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You searched for subject:(AdaBoost). Showing records 1 – 30 of 163 total matches.

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1. Prata, Thiago Lessa. Rastreamento de vídeo com aprendizagem em tempo real .

Degree: 2014, Universidade Federal de Pernambuco

 Em visão computacional, a área de rastreamento de objetos tem crescido enormemente. O aumento do poder computacional na última década tem permitido que aplicações em… (more)

Subjects/Keywords: Rastreamento; Detecção; Aprendizagem em Tempo Real; Adaboost

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Prata, T. L. (2014). Rastreamento de vídeo com aprendizagem em tempo real . (Thesis). Universidade Federal de Pernambuco. Retrieved from http://repositorio.ufpe.br/handle/123456789/11833

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Prata, Thiago Lessa. “Rastreamento de vídeo com aprendizagem em tempo real .” 2014. Thesis, Universidade Federal de Pernambuco. Accessed January 25, 2021. http://repositorio.ufpe.br/handle/123456789/11833.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Prata, Thiago Lessa. “Rastreamento de vídeo com aprendizagem em tempo real .” 2014. Web. 25 Jan 2021.

Vancouver:

Prata TL. Rastreamento de vídeo com aprendizagem em tempo real . [Internet] [Thesis]. Universidade Federal de Pernambuco; 2014. [cited 2021 Jan 25]. Available from: http://repositorio.ufpe.br/handle/123456789/11833.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Prata TL. Rastreamento de vídeo com aprendizagem em tempo real . [Thesis]. Universidade Federal de Pernambuco; 2014. Available from: http://repositorio.ufpe.br/handle/123456789/11833

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

2. Wrhel, Vladimír. Rozpoznávání vzorů v obraze pomocí AdaBoost: Pattern Recognition Using AdaBoost.

Degree: 2018, Brno University of Technology

 This paper deals about AdaBoost algorithm, which is used to create a strong classification function using a number of weak classifiers. We familiarize ourselves with… (more)

Subjects/Keywords: AdaBoost; Real AdaBoost; FloatBoost; WaldBoost; TCAcu; klasifikace; silný klasifikátor; slabý klasifikátor; OpenCV; AdaLib; AdaBoost; Real Adaboost; Floatboot; Waldboost; TCAcu; classification; strong classifier; weak classifier; OpenCV; AdaLib

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wrhel, V. (2018). Rozpoznávání vzorů v obraze pomocí AdaBoost: Pattern Recognition Using AdaBoost. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/54359

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wrhel, Vladimír. “Rozpoznávání vzorů v obraze pomocí AdaBoost: Pattern Recognition Using AdaBoost.” 2018. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/54359.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wrhel, Vladimír. “Rozpoznávání vzorů v obraze pomocí AdaBoost: Pattern Recognition Using AdaBoost.” 2018. Web. 25 Jan 2021.

Vancouver:

Wrhel V. Rozpoznávání vzorů v obraze pomocí AdaBoost: Pattern Recognition Using AdaBoost. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/54359.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wrhel V. Rozpoznávání vzorů v obraze pomocí AdaBoost: Pattern Recognition Using AdaBoost. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/54359

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Missouri University of Science and Technology

3. Novokhodko, Alexander. Neural networks with categorical valued inputs and applications to intrusion detection.

Degree: PhD, Computer Engineering, Missouri University of Science and Technology

 "The main contribution of this study is a neural network intrusion detector, built with a specific goal to minimize false alarms. The obtained performance, 0%… (more)

Subjects/Keywords: AdaBoost; Computer Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Novokhodko, A. (n.d.). Neural networks with categorical valued inputs and applications to intrusion detection. (Doctoral Dissertation). Missouri University of Science and Technology. Retrieved from https://scholarsmine.mst.edu/doctoral_dissertations/1594

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Chicago Manual of Style (16th Edition):

Novokhodko, Alexander. “Neural networks with categorical valued inputs and applications to intrusion detection.” Doctoral Dissertation, Missouri University of Science and Technology. Accessed January 25, 2021. https://scholarsmine.mst.edu/doctoral_dissertations/1594.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

MLA Handbook (7th Edition):

Novokhodko, Alexander. “Neural networks with categorical valued inputs and applications to intrusion detection.” Web. 25 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Novokhodko A. Neural networks with categorical valued inputs and applications to intrusion detection. [Internet] [Doctoral dissertation]. Missouri University of Science and Technology; [cited 2021 Jan 25]. Available from: https://scholarsmine.mst.edu/doctoral_dissertations/1594.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Council of Science Editors:

Novokhodko A. Neural networks with categorical valued inputs and applications to intrusion detection. [Doctoral Dissertation]. Missouri University of Science and Technology; Available from: https://scholarsmine.mst.edu/doctoral_dissertations/1594

Note: this citation may be lacking information needed for this citation format:
No year of publication.


Brno University of Technology

4. Melo, Jakub. RoboAuto - Detekce automobilů: RoboAuto - Car Detection.

Degree: 2019, Brno University of Technology

 This thesis deals with detection and tracking of cars viewed from behind. For the detection, Adaboost algorithm is used. The tracking is done using Kalman… (more)

Subjects/Keywords: Detekce automobilů; Sledování objektů; Adaboost; Kalmanův filtr; Car detection; Object tracking; Adaboost; Kalman filter

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Melo, J. (2019). RoboAuto - Detekce automobilů: RoboAuto - Car Detection. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/56136

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Melo, Jakub. “RoboAuto - Detekce automobilů: RoboAuto - Car Detection.” 2019. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/56136.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Melo, Jakub. “RoboAuto - Detekce automobilů: RoboAuto - Car Detection.” 2019. Web. 25 Jan 2021.

Vancouver:

Melo J. RoboAuto - Detekce automobilů: RoboAuto - Car Detection. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/56136.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Melo J. RoboAuto - Detekce automobilů: RoboAuto - Car Detection. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/56136

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

5. Hradiš, Michal. Sdílení lokální informace pro rychlejší detekci objektů: Sharing Local Information for Faster Scanning-Window Object Detection.

Degree: 2018, Brno University of Technology

 This thesis aims to improve existing scanning-window object detectors by exploiting information shared among neighboring image windows. This goal is realized by two novel methods… (more)

Subjects/Keywords: Detekce objektů; AdaBoost; WaldBoost; EnMS; Object detection; AdaBoost; WaldBoost; EnMS; neighborhood suppression; scanning-window

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hradiš, M. (2018). Sdílení lokální informace pro rychlejší detekci objektů: Sharing Local Information for Faster Scanning-Window Object Detection. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/63246

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hradiš, Michal. “Sdílení lokální informace pro rychlejší detekci objektů: Sharing Local Information for Faster Scanning-Window Object Detection.” 2018. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/63246.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hradiš, Michal. “Sdílení lokální informace pro rychlejší detekci objektů: Sharing Local Information for Faster Scanning-Window Object Detection.” 2018. Web. 25 Jan 2021.

Vancouver:

Hradiš M. Sdílení lokální informace pro rychlejší detekci objektů: Sharing Local Information for Faster Scanning-Window Object Detection. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/63246.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hradiš M. Sdílení lokální informace pro rychlejší detekci objektů: Sharing Local Information for Faster Scanning-Window Object Detection. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/63246

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

6. Chaves, Bruno Butilhão. Estudo do algoritmo AdaBoost de aprendizagem de máquina aplicado a sensores e sistemas embarcados.

Degree: Mestrado, Engenharia de Controle e Automação Mecânica, 2011, University of São Paulo

O estudo da Inteligência Artificial e de suas técnicas tem trazido grandes resultados para a evolução da tecnologia em diversas áreas. Técnicas já conhecidas como… (more)

Subjects/Keywords: AdaBoost; AdaBoost; Adulteração de combustível; Aprendizagem de máquina; Boosting; Boosting; Dispositivos embarcados; Embedded; Machine learning; Pattern recognition; Reconhecimento de padrão; Sensores

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chaves, B. B. (2011). Estudo do algoritmo AdaBoost de aprendizagem de máquina aplicado a sensores e sistemas embarcados. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/3/3152/tde-12062012-163740/ ;

Chicago Manual of Style (16th Edition):

Chaves, Bruno Butilhão. “Estudo do algoritmo AdaBoost de aprendizagem de máquina aplicado a sensores e sistemas embarcados.” 2011. Masters Thesis, University of São Paulo. Accessed January 25, 2021. http://www.teses.usp.br/teses/disponiveis/3/3152/tde-12062012-163740/ ;.

MLA Handbook (7th Edition):

Chaves, Bruno Butilhão. “Estudo do algoritmo AdaBoost de aprendizagem de máquina aplicado a sensores e sistemas embarcados.” 2011. Web. 25 Jan 2021.

Vancouver:

Chaves BB. Estudo do algoritmo AdaBoost de aprendizagem de máquina aplicado a sensores e sistemas embarcados. [Internet] [Masters thesis]. University of São Paulo; 2011. [cited 2021 Jan 25]. Available from: http://www.teses.usp.br/teses/disponiveis/3/3152/tde-12062012-163740/ ;.

Council of Science Editors:

Chaves BB. Estudo do algoritmo AdaBoost de aprendizagem de máquina aplicado a sensores e sistemas embarcados. [Masters Thesis]. University of São Paulo; 2011. Available from: http://www.teses.usp.br/teses/disponiveis/3/3152/tde-12062012-163740/ ;

7. Penne, Thomas. Développement d'un système de tracking vidéo sur caméra robotisée : Development of a video tracking system on a robotic camera.

Degree: Docteur es, Informatique, 2011, Université Blaise-Pascale, Clermont-Ferrand II

Ces dernières années se caractérisent par la prolifération des systèmes de vidéo-surveillance et par l’automatisation des traitements que ceux-ci intègrent. Parallèlement, le problème du suivi… (more)

Subjects/Keywords: Suivi d’objet; Classification; Adaboost; Ensemble Tracking; Espaces de caractéristiques; Filtrage particulaire; Object tracking; Classification; Adaboost; Ensemble Tracking; Feature spaces; Particle filtering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Penne, T. (2011). Développement d'un système de tracking vidéo sur caméra robotisée : Development of a video tracking system on a robotic camera. (Doctoral Dissertation). Université Blaise-Pascale, Clermont-Ferrand II. Retrieved from http://www.theses.fr/2011CLF22167

Chicago Manual of Style (16th Edition):

Penne, Thomas. “Développement d'un système de tracking vidéo sur caméra robotisée : Development of a video tracking system on a robotic camera.” 2011. Doctoral Dissertation, Université Blaise-Pascale, Clermont-Ferrand II. Accessed January 25, 2021. http://www.theses.fr/2011CLF22167.

MLA Handbook (7th Edition):

Penne, Thomas. “Développement d'un système de tracking vidéo sur caméra robotisée : Development of a video tracking system on a robotic camera.” 2011. Web. 25 Jan 2021.

Vancouver:

Penne T. Développement d'un système de tracking vidéo sur caméra robotisée : Development of a video tracking system on a robotic camera. [Internet] [Doctoral dissertation]. Université Blaise-Pascale, Clermont-Ferrand II; 2011. [cited 2021 Jan 25]. Available from: http://www.theses.fr/2011CLF22167.

Council of Science Editors:

Penne T. Développement d'un système de tracking vidéo sur caméra robotisée : Development of a video tracking system on a robotic camera. [Doctoral Dissertation]. Université Blaise-Pascale, Clermont-Ferrand II; 2011. Available from: http://www.theses.fr/2011CLF22167


Brno University of Technology

8. Chmiel, Filip. Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position.

Degree: 2020, Brno University of Technology

 This paper presents the method for a head pose and orientation detection based on computer vision techniques. The method is based on the AdaBoost approach… (more)

Subjects/Keywords: uživatelská rozhraní; detekce obličeje; počítačové vidění; AdaBoost; optický tok; user interface; face detection; computer vision; AdaBoost; optical flow

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chmiel, F. (2020). Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/189682

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chmiel, Filip. “Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position.” 2020. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/189682.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chmiel, Filip. “Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position.” 2020. Web. 25 Jan 2021.

Vancouver:

Chmiel F. Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/189682.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chmiel F. Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/189682

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

9. Vojáček, Cyril. Rozpoznání obličeje: Face Recognition.

Degree: 2019, Brno University of Technology

 This thesis is about face detection and recognition from video. Main emphasis is on computational speed, so it can be used for a real-time processing.… (more)

Subjects/Keywords: obličej; detekce; rozpoznávání; NPD příznak; Viola & Jones; Adaboost; OpenTLD; face; detection; recognition; NPD feature; Viola & Jones; Adaboost; OpenTLD

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Vojáček, C. (2019). Rozpoznání obličeje: Face Recognition. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/53386

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Vojáček, Cyril. “Rozpoznání obličeje: Face Recognition.” 2019. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/53386.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Vojáček, Cyril. “Rozpoznání obličeje: Face Recognition.” 2019. Web. 25 Jan 2021.

Vancouver:

Vojáček C. Rozpoznání obličeje: Face Recognition. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/53386.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vojáček C. Rozpoznání obličeje: Face Recognition. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/53386

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

10. Pomykal, Antonín. Detekce automobilů v obraze: Detection of Vehicles in Image.

Degree: 2019, Brno University of Technology

 This work deals with the possibility of detection of cars in the image using the characteristics of  cars with custom created image features , which… (more)

Subjects/Keywords: detekce automobilů; OpenCV; Adaboost; Haarovy příznaky; obrazové příznaky; car detection; OpenCV; Adaboost; Haar features; image features

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Pomykal, A. (2019). Detekce automobilů v obraze: Detection of Vehicles in Image. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/56021

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Pomykal, Antonín. “Detekce automobilů v obraze: Detection of Vehicles in Image.” 2019. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/56021.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Pomykal, Antonín. “Detekce automobilů v obraze: Detection of Vehicles in Image.” 2019. Web. 25 Jan 2021.

Vancouver:

Pomykal A. Detekce automobilů v obraze: Detection of Vehicles in Image. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/56021.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pomykal A. Detekce automobilů v obraze: Detection of Vehicles in Image. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/56021

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

11. Raszka, Aleš. Klasifikace vozidel s použitím radaru: Vehicle Classification Using Radar.

Degree: 2019, Brno University of Technology

 This Master thesis deals with usage of radar signal for vehicle classification. The thesis uses radar modules with continuous wave based on Doppler effect. Radar… (more)

Subjects/Keywords: Dopplerův jev; radar; zpracování signálu; klasifikace; vozidlo; SVM; Adaboost; Doppler effect; radar; signal processing; classification; vehicle; SVM; Adaboost

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Raszka, A. (2019). Klasifikace vozidel s použitím radaru: Vehicle Classification Using Radar. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/69590

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Raszka, Aleš. “Klasifikace vozidel s použitím radaru: Vehicle Classification Using Radar.” 2019. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/69590.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Raszka, Aleš. “Klasifikace vozidel s použitím radaru: Vehicle Classification Using Radar.” 2019. Web. 25 Jan 2021.

Vancouver:

Raszka A. Klasifikace vozidel s použitím radaru: Vehicle Classification Using Radar. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/69590.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Raszka A. Klasifikace vozidel s použitím radaru: Vehicle Classification Using Radar. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/69590

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

12. Tretter, Zdeněk. Klasifikátor biometrických obrazových dat: Biometric Image Data Classifier.

Degree: 2019, Brno University of Technology

 The aim of this thesis is to design and implement fingerprint classifier, which classifies the fingerprints based on the scanner used. Reader is presented with… (more)

Subjects/Keywords: otisk prstu; klasifikace; AdaBoost; kaskáda klasifikátorů; obrazové filtry; C++; OpenCV; fingerprint; classification; AdaBoost; cascade of classifiers; image filters; C++; OpenCV

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Tretter, Z. (2019). Klasifikátor biometrických obrazových dat: Biometric Image Data Classifier. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/56618

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Tretter, Zdeněk. “Klasifikátor biometrických obrazových dat: Biometric Image Data Classifier.” 2019. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/56618.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Tretter, Zdeněk. “Klasifikátor biometrických obrazových dat: Biometric Image Data Classifier.” 2019. Web. 25 Jan 2021.

Vancouver:

Tretter Z. Klasifikátor biometrických obrazových dat: Biometric Image Data Classifier. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/56618.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tretter Z. Klasifikátor biometrických obrazových dat: Biometric Image Data Classifier. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/56618

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

13. Charvát, Jaroslav. Ovládání počítače pomocí gest: Human-Machine Interface Based on Gestures.

Degree: 2019, Brno University of Technology

 Master's thesis "Human-Machine Interface Based on Gestures" depicts the theoretical background of the computer vision and gesture recognition. It describes more in detail different methods… (more)

Subjects/Keywords: Počítačové vidění; detekce obličeje; rozpoznávání gest; AdaBoost; PCA.; Computer vision; face detection; gesture recognition; AdaBoost; PCA.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Charvát, J. (2019). Ovládání počítače pomocí gest: Human-Machine Interface Based on Gestures. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/54065

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Charvát, Jaroslav. “Ovládání počítače pomocí gest: Human-Machine Interface Based on Gestures.” 2019. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/54065.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Charvát, Jaroslav. “Ovládání počítače pomocí gest: Human-Machine Interface Based on Gestures.” 2019. Web. 25 Jan 2021.

Vancouver:

Charvát J. Ovládání počítače pomocí gest: Human-Machine Interface Based on Gestures. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/54065.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Charvát J. Ovládání počítače pomocí gest: Human-Machine Interface Based on Gestures. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/54065

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

14. Juránek, Roman. Akcelerace detekce objektů pomocí klasifikátorů: Acceleration of Object Detection Using Classifiers.

Degree: 2018, Brno University of Technology

 Detection of objects in computer vision is a complex task. One of most popular and well explored  approaches is the use of statistical classifiers and… (more)

Subjects/Keywords: Detekce objektů; AdaBoost; WaldBoost; Akcelerace; SIMD; Minimalizace ceny; Object Detection; AdaBoost; WaldBoost; Acceleration; SIMD; Cost Minimization

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APA (6th Edition):

Juránek, R. (2018). Akcelerace detekce objektů pomocí klasifikátorů: Acceleration of Object Detection Using Classifiers. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/63272

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Juránek, Roman. “Akcelerace detekce objektů pomocí klasifikátorů: Acceleration of Object Detection Using Classifiers.” 2018. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/63272.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Juránek, Roman. “Akcelerace detekce objektů pomocí klasifikátorů: Acceleration of Object Detection Using Classifiers.” 2018. Web. 25 Jan 2021.

Vancouver:

Juránek R. Akcelerace detekce objektů pomocí klasifikátorů: Acceleration of Object Detection Using Classifiers. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/63272.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Juránek R. Akcelerace detekce objektů pomocí klasifikátorů: Acceleration of Object Detection Using Classifiers. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/63272

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

15. Čepl, Radek. Optimalizace algoritmů pro zpracování obrazu v C++ pomocí šablon: Image Processing Algorithms Optimization Using C++ Templates.

Degree: 2019, Brno University of Technology

 Bachelor's thesis deals with image processing algorithm AdaBoost optimalization using C++ templates. Head aim of this thesis is effective evaluation of Haar Features with constant… (more)

Subjects/Keywords: AdaBoost; Haarovy příznaky; Integrální obraz; Klasifikátor; C++ šablony; AdaBoost; Haar features; Integral image; Classifier; C++ templates

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Čepl, R. (2019). Optimalizace algoritmů pro zpracování obrazu v C++ pomocí šablon: Image Processing Algorithms Optimization Using C++ Templates. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/55594

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Čepl, Radek. “Optimalizace algoritmů pro zpracování obrazu v C++ pomocí šablon: Image Processing Algorithms Optimization Using C++ Templates.” 2019. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/55594.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Čepl, Radek. “Optimalizace algoritmů pro zpracování obrazu v C++ pomocí šablon: Image Processing Algorithms Optimization Using C++ Templates.” 2019. Web. 25 Jan 2021.

Vancouver:

Čepl R. Optimalizace algoritmů pro zpracování obrazu v C++ pomocí šablon: Image Processing Algorithms Optimization Using C++ Templates. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/55594.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Čepl R. Optimalizace algoritmů pro zpracování obrazu v C++ pomocí šablon: Image Processing Algorithms Optimization Using C++ Templates. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/55594

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

16. Šašinka, Ondřej. Detekce obličeje: Face Detection.

Degree: 2019, Brno University of Technology

 This MSc Thesis deals with face detection in image. In this approach, facial features (eyes, nose, mouth corners) are detected first and then joined to… (more)

Subjects/Keywords: Detekce obličeje; detekce obličejových rysů; AdaBoost; Haarovy vlnky; integrální obraz.; Face detection; facial features detection; AdaBoost; Haar wavelets; integral image.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Šašinka, O. (2019). Detekce obličeje: Face Detection. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/53827

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Šašinka, Ondřej. “Detekce obličeje: Face Detection.” 2019. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/53827.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Šašinka, Ondřej. “Detekce obličeje: Face Detection.” 2019. Web. 25 Jan 2021.

Vancouver:

Šašinka O. Detekce obličeje: Face Detection. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/53827.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Šašinka O. Detekce obličeje: Face Detection. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/53827

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

17. Pospíšil, Josef. Digitalizace historických map: Ancient Maps Digitizing.

Degree: 2019, Brno University of Technology

This work is about processing of historical maps, especially their digitizing and vectorization. The main focuses of this project are maps from the second historical military mapping and finding methods useful for removing texts from these maps. Advisors/Committee Members: Španěl, Michal (advisor), Šilhavá, Jana (referee).

Subjects/Keywords: historické mapy; druhé vojenské mapování; digitalizace; AdaBoost; historical maps; the second historical military mapping; digitize; AdaBoost

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APA (6th Edition):

Pospíšil, J. (2019). Digitalizace historických map: Ancient Maps Digitizing. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/53177

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Pospíšil, Josef. “Digitalizace historických map: Ancient Maps Digitizing.” 2019. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/53177.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Pospíšil, Josef. “Digitalizace historických map: Ancient Maps Digitizing.” 2019. Web. 25 Jan 2021.

Vancouver:

Pospíšil J. Digitalizace historických map: Ancient Maps Digitizing. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/53177.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pospíšil J. Digitalizace historických map: Ancient Maps Digitizing. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/53177

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

18. Juránek, Roman. Rozpoznání vzorů v obraze pomocí klasifikátorů: Pattern Recognition in Image Using Classifiers.

Degree: 2020, Brno University of Technology

 An AdaBoost algorithm for construction of strong classifier from several weak hypotesis will be presented in this work. Theoretical background of the algorithm and the… (more)

Subjects/Keywords: Rozpoznávání vzorů; AdaBoost; WaldBoost; Klasifikace; Detekce; Obrazové Příznaky; Pattern recognition; AdaBoost; WaldBoost; Classification; Detection; Image Features

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Juránek, R. (2020). Rozpoznání vzorů v obraze pomocí klasifikátorů: Pattern Recognition in Image Using Classifiers. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/187992

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Juránek, Roman. “Rozpoznání vzorů v obraze pomocí klasifikátorů: Pattern Recognition in Image Using Classifiers.” 2020. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/187992.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Juránek, Roman. “Rozpoznání vzorů v obraze pomocí klasifikátorů: Pattern Recognition in Image Using Classifiers.” 2020. Web. 25 Jan 2021.

Vancouver:

Juránek R. Rozpoznání vzorů v obraze pomocí klasifikátorů: Pattern Recognition in Image Using Classifiers. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/187992.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Juránek R. Rozpoznání vzorů v obraze pomocí klasifikátorů: Pattern Recognition in Image Using Classifiers. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/187992

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

19. Juránek, Roman. Rozpoznání vzorů v obraze pomocí klasifikátorů: Pattern Recognition in Image Using Classifiers.

Degree: 2020, Brno University of Technology

 An AdaBoost algorithm for construction of strong classifier from several weak hypotesis will be presented in this work. Theoretical background of the algorithm and the… (more)

Subjects/Keywords: Rozpoznávání vzorů; AdaBoost; WaldBoost; Klasifikace; Detekce; Obrazové Příznaky; Pattern recognition; AdaBoost; WaldBoost; Classification; Detection; Image Features

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Juránek, R. (2020). Rozpoznání vzorů v obraze pomocí klasifikátorů: Pattern Recognition in Image Using Classifiers. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/53944

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Juránek, Roman. “Rozpoznání vzorů v obraze pomocí klasifikátorů: Pattern Recognition in Image Using Classifiers.” 2020. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/53944.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Juránek, Roman. “Rozpoznání vzorů v obraze pomocí klasifikátorů: Pattern Recognition in Image Using Classifiers.” 2020. Web. 25 Jan 2021.

Vancouver:

Juránek R. Rozpoznání vzorů v obraze pomocí klasifikátorů: Pattern Recognition in Image Using Classifiers. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/53944.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Juránek R. Rozpoznání vzorů v obraze pomocí klasifikátorů: Pattern Recognition in Image Using Classifiers. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/53944

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

20. Mrnuštík, Michal. Boosting a evoluční algoritmy: Boosting and Evolution.

Degree: 2020, Brno University of Technology

 This thesis introduces combination of the AdaBoost and the evolutionary algorithm. The evolutionary algorithm is used to find linear combination of Haar features. This linear… (more)

Subjects/Keywords: boosting; adaboost; evoluční algoritmy; rozpoznávání vzorů; haarovy příznaky; boosting; adaboost; evolutionary algorithms; pattern recognition; haar features

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mrnuštík, M. (2020). Boosting a evoluční algoritmy: Boosting and Evolution. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/188193

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mrnuštík, Michal. “Boosting a evoluční algoritmy: Boosting and Evolution.” 2020. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/188193.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mrnuštík, Michal. “Boosting a evoluční algoritmy: Boosting and Evolution.” 2020. Web. 25 Jan 2021.

Vancouver:

Mrnuštík M. Boosting a evoluční algoritmy: Boosting and Evolution. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/188193.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mrnuštík M. Boosting a evoluční algoritmy: Boosting and Evolution. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/188193

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

21. Chmiel, Filip. Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position.

Degree: 2020, Brno University of Technology

 This paper presents the method for a head pose and orientation detection based on computer vision techniques. The method is based on the AdaBoost approach… (more)

Subjects/Keywords: uživatelská rozhraní; detekce obličeje; počítačové vidění; AdaBoost; optický tok; user interface; face detection; computer vision; AdaBoost; optical flow

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APA (6th Edition):

Chmiel, F. (2020). Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/188257

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chmiel, Filip. “Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position.” 2020. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/188257.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chmiel, Filip. “Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position.” 2020. Web. 25 Jan 2021.

Vancouver:

Chmiel F. Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/188257.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chmiel F. Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/188257

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

22. Králík, Martin. Detekce objektů v obraze s pomocí rozšířené sady Haarových příznaků a histogramu: Object detection in images using extended set of Haar-like features and histogram-based method.

Degree: 2019, Brno University of Technology

 This diploma thesis is focused on detection in images using extended set of Haar-like features and histogram-based method. At first is introduced a basic concept… (more)

Subjects/Keywords: Adaboost; počítačové vidění; Diffusion distance; příznaky; histogramy; chodci; tepny; Adaboost; computer vision; Diffusion distance; features; histogram; pedestrians; artery

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Králík, M. (2019). Detekce objektů v obraze s pomocí rozšířené sady Haarových příznaků a histogramu: Object detection in images using extended set of Haar-like features and histogram-based method. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/9497

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Králík, Martin. “Detekce objektů v obraze s pomocí rozšířené sady Haarových příznaků a histogramu: Object detection in images using extended set of Haar-like features and histogram-based method.” 2019. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/9497.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Králík, Martin. “Detekce objektů v obraze s pomocí rozšířené sady Haarových příznaků a histogramu: Object detection in images using extended set of Haar-like features and histogram-based method.” 2019. Web. 25 Jan 2021.

Vancouver:

Králík M. Detekce objektů v obraze s pomocí rozšířené sady Haarových příznaků a histogramu: Object detection in images using extended set of Haar-like features and histogram-based method. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/9497.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Králík M. Detekce objektů v obraze s pomocí rozšířené sady Haarových příznaků a histogramu: Object detection in images using extended set of Haar-like features and histogram-based method. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/9497

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

23. Wiewiorka, Petr. Ovládání počítače gesty: Video-Based Human-Computer Interface.

Degree: 2016, Brno University of Technology

 This bachelor's thesis descripts a way of controlling a computer by hand gestures. Picture is taken from web camera, in which search for a position… (more)

Subjects/Keywords: Zpracování obrazu; ovládání počítače gesty; adaboost; haartraining; OpenCV; Image processing; gesture computer controlling; adaboost; haartraining; OpenCV

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wiewiorka, P. (2016). Ovládání počítače gesty: Video-Based Human-Computer Interface. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/55441

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wiewiorka, Petr. “Ovládání počítače gesty: Video-Based Human-Computer Interface.” 2016. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/55441.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wiewiorka, Petr. “Ovládání počítače gesty: Video-Based Human-Computer Interface.” 2016. Web. 25 Jan 2021.

Vancouver:

Wiewiorka P. Ovládání počítače gesty: Video-Based Human-Computer Interface. [Internet] [Thesis]. Brno University of Technology; 2016. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/55441.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wiewiorka P. Ovládání počítače gesty: Video-Based Human-Computer Interface. [Thesis]. Brno University of Technology; 2016. Available from: http://hdl.handle.net/11012/55441

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

24. Vykoupil, Pavel. Inteligentní klasifikace příznaků pro podporu diagnostiky glaukomu: Intelligent features classification aimed to support diagnosis of glaucoma.

Degree: 2018, Brno University of Technology

 This bachelor thesis deals with inteligent features classification aimed to support diagnosis of glaucoma. First part focuses on eye anatomy and disease called glaucoma. In… (more)

Subjects/Keywords: klasifikace; příznaky; diagnostika; glaukom; texturní analýza; neuronové sítě; HoKashyap; AdaBoost.; classification; attributes; diagnostics; glaucoma; texture analysis; neural networks; HoKashyap; AdaBoost.

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APA (6th Edition):

Vykoupil, P. (2018). Inteligentní klasifikace příznaků pro podporu diagnostiky glaukomu: Intelligent features classification aimed to support diagnosis of glaucoma. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/12401

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Vykoupil, Pavel. “Inteligentní klasifikace příznaků pro podporu diagnostiky glaukomu: Intelligent features classification aimed to support diagnosis of glaucoma.” 2018. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/12401.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Vykoupil, Pavel. “Inteligentní klasifikace příznaků pro podporu diagnostiky glaukomu: Intelligent features classification aimed to support diagnosis of glaucoma.” 2018. Web. 25 Jan 2021.

Vancouver:

Vykoupil P. Inteligentní klasifikace příznaků pro podporu diagnostiky glaukomu: Intelligent features classification aimed to support diagnosis of glaucoma. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/12401.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vykoupil P. Inteligentní klasifikace příznaků pro podporu diagnostiky glaukomu: Intelligent features classification aimed to support diagnosis of glaucoma. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/12401

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

25. Mrnuštík, Michal. Boosting a evoluční algoritmy: Boosting and Evolution.

Degree: 2020, Brno University of Technology

 This thesis introduces combination of the AdaBoost and the evolutionary algorithm. The evolutionary algorithm is used to find linear combination of Haar features. This linear… (more)

Subjects/Keywords: boosting; adaboost; evoluční algoritmy; rozpoznávání vzorů; haarovy příznaky; boosting; adaboost; evolutionary algorithms; pattern recognition; haar features

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mrnuštík, M. (2020). Boosting a evoluční algoritmy: Boosting and Evolution. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/55453

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mrnuštík, Michal. “Boosting a evoluční algoritmy: Boosting and Evolution.” 2020. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/55453.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mrnuštík, Michal. “Boosting a evoluční algoritmy: Boosting and Evolution.” 2020. Web. 25 Jan 2021.

Vancouver:

Mrnuštík M. Boosting a evoluční algoritmy: Boosting and Evolution. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/55453.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mrnuštík M. Boosting a evoluční algoritmy: Boosting and Evolution. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/55453

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

26. Chmiel, Filip. Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position.

Degree: 2020, Brno University of Technology

 This paper presents the method for a head pose and orientation detection based on computer vision techniques. The method is based on the AdaBoost approach… (more)

Subjects/Keywords: uživatelská rozhraní; detekce obličeje; počítačové vidění; AdaBoost; optický tok; user interface; face detection; computer vision; AdaBoost; optical flow

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APA (6th Edition):

Chmiel, F. (2020). Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/55810

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chmiel, Filip. “Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position.” 2020. Thesis, Brno University of Technology. Accessed January 25, 2021. http://hdl.handle.net/11012/55810.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chmiel, Filip. “Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position.” 2020. Web. 25 Jan 2021.

Vancouver:

Chmiel F. Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2021 Jan 25]. Available from: http://hdl.handle.net/11012/55810.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chmiel F. Rozhraní počítače využívající polohu hlavy uživatele: Computer Interface Based on User's Head Position. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/55810

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


NSYSU

27. Ciou, Yue-Sheng. Object Recognition System Design in Regions of Interest Based on AdaBoost Algorithm.

Degree: Master, Mechanical and Electro-Mechanical Engineering, 2015, NSYSU

 In recent years, vehicle safety has become an important issue in modern automotive technology. This research proposes an object recognition system based on AdaBoost algorithm,… (more)

Subjects/Keywords: neural network; image processing; AdaBoost; OpenCV; system integration

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ciou, Y. (2015). Object Recognition System Design in Regions of Interest Based on AdaBoost Algorithm. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0719114-230542

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ciou, Yue-Sheng. “Object Recognition System Design in Regions of Interest Based on AdaBoost Algorithm.” 2015. Thesis, NSYSU. Accessed January 25, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0719114-230542.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ciou, Yue-Sheng. “Object Recognition System Design in Regions of Interest Based on AdaBoost Algorithm.” 2015. Web. 25 Jan 2021.

Vancouver:

Ciou Y. Object Recognition System Design in Regions of Interest Based on AdaBoost Algorithm. [Internet] [Thesis]. NSYSU; 2015. [cited 2021 Jan 25]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0719114-230542.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ciou Y. Object Recognition System Design in Regions of Interest Based on AdaBoost Algorithm. [Thesis]. NSYSU; 2015. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0719114-230542

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


NSYSU

28. Lin, Hung-shyuan. Applying The Concept of Fuzzy Logic to Inverse Reinforcement Learning.

Degree: Master, Electrical Engineering, 2015, NSYSU

 Itâs a study on Reinforcement Learning, learning interaction of agents and dynamic environment to get reward function R, and update the policy, converge learning and… (more)

Subjects/Keywords: Inverse reinforcement learning; Reward function; Fuzzy; Reinforcement learning; AdaBoost; Apprenticeship learning

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APA (6th Edition):

Lin, H. (2015). Applying The Concept of Fuzzy Logic to Inverse Reinforcement Learning. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1025115-185021

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lin, Hung-shyuan. “Applying The Concept of Fuzzy Logic to Inverse Reinforcement Learning.” 2015. Thesis, NSYSU. Accessed January 25, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1025115-185021.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lin, Hung-shyuan. “Applying The Concept of Fuzzy Logic to Inverse Reinforcement Learning.” 2015. Web. 25 Jan 2021.

Vancouver:

Lin H. Applying The Concept of Fuzzy Logic to Inverse Reinforcement Learning. [Internet] [Thesis]. NSYSU; 2015. [cited 2021 Jan 25]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1025115-185021.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lin H. Applying The Concept of Fuzzy Logic to Inverse Reinforcement Learning. [Thesis]. NSYSU; 2015. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1025115-185021

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Tampere University

29. PAUKKERI, RAUNO. Tilastolliset oppimisyhdistelmät asiakasvaihtuvuuden ennustamisessa .

Degree: 2013, Tampere University

 Tämän tutkielman tarkoituksena on selvittää ja vertailla erilaisia tilastollisia oppimisyhdistelmiä erään suomalaisen teleoperaattorin asiakasvaihtuvuuden ennustamisessa. Tutkielmassa tarkastellaan myös, onko opetusaineiston painottamisella vaikutusta asiakasvaihtuvuuden ennustamisen tarkkuuteen.… (more)

Subjects/Keywords: Bagging; Boosting; Real AdaBoost; Gradient Boosting; satunnaismetsä; päätöspuut

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APA (6th Edition):

PAUKKERI, R. (2013). Tilastolliset oppimisyhdistelmät asiakasvaihtuvuuden ennustamisessa . (Masters Thesis). Tampere University. Retrieved from https://trepo.tuni.fi/handle/10024/94855

Chicago Manual of Style (16th Edition):

PAUKKERI, RAUNO. “Tilastolliset oppimisyhdistelmät asiakasvaihtuvuuden ennustamisessa .” 2013. Masters Thesis, Tampere University. Accessed January 25, 2021. https://trepo.tuni.fi/handle/10024/94855.

MLA Handbook (7th Edition):

PAUKKERI, RAUNO. “Tilastolliset oppimisyhdistelmät asiakasvaihtuvuuden ennustamisessa .” 2013. Web. 25 Jan 2021.

Vancouver:

PAUKKERI R. Tilastolliset oppimisyhdistelmät asiakasvaihtuvuuden ennustamisessa . [Internet] [Masters thesis]. Tampere University; 2013. [cited 2021 Jan 25]. Available from: https://trepo.tuni.fi/handle/10024/94855.

Council of Science Editors:

PAUKKERI R. Tilastolliset oppimisyhdistelmät asiakasvaihtuvuuden ennustamisessa . [Masters Thesis]. Tampere University; 2013. Available from: https://trepo.tuni.fi/handle/10024/94855


Uppsala University

30. Virkkala, Linda. Modelling of patterns between operational data, diagnostic trouble codes and workshop history using big data and machine learning.

Degree: Computing Science, 2016, Uppsala University

  The work presented in this thesis is part of a large research and development project on condition-based maintenance for heavy trucks and buses at… (more)

Subjects/Keywords: Data mining; random forest; adaboost; error codes; Computer Sciences; Datavetenskap (datalogi)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Virkkala, L. (2016). Modelling of patterns between operational data, diagnostic trouble codes and workshop history using big data and machine learning. (Thesis). Uppsala University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-279823

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Virkkala, Linda. “Modelling of patterns between operational data, diagnostic trouble codes and workshop history using big data and machine learning.” 2016. Thesis, Uppsala University. Accessed January 25, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-279823.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Virkkala, Linda. “Modelling of patterns between operational data, diagnostic trouble codes and workshop history using big data and machine learning.” 2016. Web. 25 Jan 2021.

Vancouver:

Virkkala L. Modelling of patterns between operational data, diagnostic trouble codes and workshop history using big data and machine learning. [Internet] [Thesis]. Uppsala University; 2016. [cited 2021 Jan 25]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-279823.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Virkkala L. Modelling of patterns between operational data, diagnostic trouble codes and workshop history using big data and machine learning. [Thesis]. Uppsala University; 2016. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-279823

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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