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You searched for subject:( object detection). Showing records 1 – 30 of 527 total matches.

[1] [2] [3] [4] [5] … [18]

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University of Edinburgh

1. Modolo, Davide. Advances in detecting object classes and their semantic parts.

Degree: PhD, 2017, University of Edinburgh

Object classes are central to computer vision and have been the focus of substantial research in the last fifteen years. This thesis addresses the tasks… (more)

Subjects/Keywords: 006.3; object detection; part detection

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APA (6th Edition):

Modolo, D. (2017). Advances in detecting object classes and their semantic parts. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/23472

Chicago Manual of Style (16th Edition):

Modolo, Davide. “Advances in detecting object classes and their semantic parts.” 2017. Doctoral Dissertation, University of Edinburgh. Accessed September 19, 2019. http://hdl.handle.net/1842/23472.

MLA Handbook (7th Edition):

Modolo, Davide. “Advances in detecting object classes and their semantic parts.” 2017. Web. 19 Sep 2019.

Vancouver:

Modolo D. Advances in detecting object classes and their semantic parts. [Internet] [Doctoral dissertation]. University of Edinburgh; 2017. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/1842/23472.

Council of Science Editors:

Modolo D. Advances in detecting object classes and their semantic parts. [Doctoral Dissertation]. University of Edinburgh; 2017. Available from: http://hdl.handle.net/1842/23472


University of Louisville

2. Farag, Amal A. Modeling small objects under uncertainties : novel algorithms and applications.

Degree: PhD, 2012, University of Louisville

 Active Shape Models (ASM), Active Appearance Models (AAM) and Active Tensor Models (ATM) are common approaches to model elastic (deformable) objects. These models require an… (more)

Subjects/Keywords: Object modeling; Object categorization; Object segmentation; Lung nodules; Object detection

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APA (6th Edition):

Farag, A. A. (2012). Modeling small objects under uncertainties : novel algorithms and applications. (Doctoral Dissertation). University of Louisville. Retrieved from 10.18297/etd/423 ; https://ir.library.louisville.edu/etd/423

Chicago Manual of Style (16th Edition):

Farag, Amal A. “Modeling small objects under uncertainties : novel algorithms and applications.” 2012. Doctoral Dissertation, University of Louisville. Accessed September 19, 2019. 10.18297/etd/423 ; https://ir.library.louisville.edu/etd/423.

MLA Handbook (7th Edition):

Farag, Amal A. “Modeling small objects under uncertainties : novel algorithms and applications.” 2012. Web. 19 Sep 2019.

Vancouver:

Farag AA. Modeling small objects under uncertainties : novel algorithms and applications. [Internet] [Doctoral dissertation]. University of Louisville; 2012. [cited 2019 Sep 19]. Available from: 10.18297/etd/423 ; https://ir.library.louisville.edu/etd/423.

Council of Science Editors:

Farag AA. Modeling small objects under uncertainties : novel algorithms and applications. [Doctoral Dissertation]. University of Louisville; 2012. Available from: 10.18297/etd/423 ; https://ir.library.louisville.edu/etd/423


University of Victoria

3. Moria, Kawther. Computer vision-based detection of fire and violent actions performed by individuals in videos acquired with handheld devices.

Degree: Department of Computer Science, 2016, University of Victoria

 Advances in social networks and multimedia technologies greatly facilitate the recording and sharing of video data on violent social and/or political events via In- ternet.… (more)

Subjects/Keywords: Object detection; Fire detection; Object recognition; Violent scene detection; Crowd recognition.

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APA (6th Edition):

Moria, K. (2016). Computer vision-based detection of fire and violent actions performed by individuals in videos acquired with handheld devices. (Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/7423

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):

Moria, Kawther. “Computer vision-based detection of fire and violent actions performed by individuals in videos acquired with handheld devices.” 2016. Thesis, University of Victoria. Accessed September 19, 2019. http://hdl.handle.net/1828/7423.

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

MLA Handbook (7th Edition):

Moria, Kawther. “Computer vision-based detection of fire and violent actions performed by individuals in videos acquired with handheld devices.” 2016. Web. 19 Sep 2019.

Vancouver:

Moria K. Computer vision-based detection of fire and violent actions performed by individuals in videos acquired with handheld devices. [Internet] [Thesis]. University of Victoria; 2016. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/1828/7423.

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

Council of Science Editors:

Moria K. Computer vision-based detection of fire and violent actions performed by individuals in videos acquired with handheld devices. [Thesis]. University of Victoria; 2016. Available from: http://hdl.handle.net/1828/7423

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


Georgia Tech

4. Humayun, Ahmad. Detection and Incremental Object Learning in Videos.

Degree: PhD, Computer Science, 2018, Georgia Tech

 Unlike state-of-the-art batch machine learning methods, children have a remarkable facility for learning visual representations of objects through a combination of self-directed visual exploration and… (more)

Subjects/Keywords: Video Object Detection; Incremental Learning; Object Proposals

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APA (6th Edition):

Humayun, A. (2018). Detection and Incremental Object Learning in Videos. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61614

Chicago Manual of Style (16th Edition):

Humayun, Ahmad. “Detection and Incremental Object Learning in Videos.” 2018. Doctoral Dissertation, Georgia Tech. Accessed September 19, 2019. http://hdl.handle.net/1853/61614.

MLA Handbook (7th Edition):

Humayun, Ahmad. “Detection and Incremental Object Learning in Videos.” 2018. Web. 19 Sep 2019.

Vancouver:

Humayun A. Detection and Incremental Object Learning in Videos. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/1853/61614.

Council of Science Editors:

Humayun A. Detection and Incremental Object Learning in Videos. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61614


NSYSU

5. Lee, Allen. A VQ Coding Based Method for Object Detection.

Degree: Master, Mechanical and Electro-Mechanical Engineering, 2002, NSYSU

none Advisors/Committee Members: Yen,Chen-Wen (committee member), Cheng,Chi-Cheng (chair), Gou-Jen Wang (chair).

Subjects/Keywords: Object Detection

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APA (6th Edition):

Lee, A. (2002). A VQ Coding Based Method for Object Detection. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716102-160939

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):

Lee, Allen. “A VQ Coding Based Method for Object Detection.” 2002. Thesis, NSYSU. Accessed September 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716102-160939.

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

MLA Handbook (7th Edition):

Lee, Allen. “A VQ Coding Based Method for Object Detection.” 2002. Web. 19 Sep 2019.

Vancouver:

Lee A. A VQ Coding Based Method for Object Detection. [Internet] [Thesis]. NSYSU; 2002. [cited 2019 Sep 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716102-160939.

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

Council of Science Editors:

Lee A. A VQ Coding Based Method for Object Detection. [Thesis]. NSYSU; 2002. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0716102-160939

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


Universitat Autònoma de Barcelona

6. Pedersoli, Marco. Hierarchical multiresolution models for fast object detection.

Degree: Departament de Ciències de la Computació, 2012, Universitat Autònoma de Barcelona

 Day by day, the ability to automatically detect and recognize objects in unconstrained images is becoming more and more important. From security systems and robots,… (more)

Subjects/Keywords: Object detection; Multiresolution; Tecnologies; 004

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APA (6th Edition):

Pedersoli, M. (2012). Hierarchical multiresolution models for fast object detection. (Thesis). Universitat Autònoma de Barcelona. Retrieved from http://hdl.handle.net/10803/286175

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):

Pedersoli, Marco. “Hierarchical multiresolution models for fast object detection.” 2012. Thesis, Universitat Autònoma de Barcelona. Accessed September 19, 2019. http://hdl.handle.net/10803/286175.

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

MLA Handbook (7th Edition):

Pedersoli, Marco. “Hierarchical multiresolution models for fast object detection.” 2012. Web. 19 Sep 2019.

Vancouver:

Pedersoli M. Hierarchical multiresolution models for fast object detection. [Internet] [Thesis]. Universitat Autònoma de Barcelona; 2012. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10803/286175.

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

Council of Science Editors:

Pedersoli M. Hierarchical multiresolution models for fast object detection. [Thesis]. Universitat Autònoma de Barcelona; 2012. Available from: http://hdl.handle.net/10803/286175

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


Halmstad University

7. Mühlfellner, Peter. Selection, Analysis and Implementationof Image-based Feature Extraction Approaches for a Heterogenous, Modular and FPGA-based Architecture for Camera-based Driver Assistance Systems.

Degree: Intelligent systems (IS-lab), 2011, Halmstad University

  We propose a scalable and fexible hardware architecture for the extraction of image features, used in conjunction with an attentional cascade classifier for appearance-based… (more)

Subjects/Keywords: Object Detection; Feature Extraction; FPGA

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APA (6th Edition):

Mühlfellner, P. (2011). Selection, Analysis and Implementationof Image-based Feature Extraction Approaches for a Heterogenous, Modular and FPGA-based Architecture for Camera-based Driver Assistance Systems. (Thesis). Halmstad University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-16377

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):

Mühlfellner, Peter. “Selection, Analysis and Implementationof Image-based Feature Extraction Approaches for a Heterogenous, Modular and FPGA-based Architecture for Camera-based Driver Assistance Systems.” 2011. Thesis, Halmstad University. Accessed September 19, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-16377.

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

MLA Handbook (7th Edition):

Mühlfellner, Peter. “Selection, Analysis and Implementationof Image-based Feature Extraction Approaches for a Heterogenous, Modular and FPGA-based Architecture for Camera-based Driver Assistance Systems.” 2011. Web. 19 Sep 2019.

Vancouver:

Mühlfellner P. Selection, Analysis and Implementationof Image-based Feature Extraction Approaches for a Heterogenous, Modular and FPGA-based Architecture for Camera-based Driver Assistance Systems. [Internet] [Thesis]. Halmstad University; 2011. [cited 2019 Sep 19]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-16377.

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

Council of Science Editors:

Mühlfellner P. Selection, Analysis and Implementationof Image-based Feature Extraction Approaches for a Heterogenous, Modular and FPGA-based Architecture for Camera-based Driver Assistance Systems. [Thesis]. Halmstad University; 2011. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-16377

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


University of Bridgeport

8. Abualkibash, Munther Hamad. A Near Real-Time, Highly Scalable, Parallel and Distributed Adaptive Object Detection and Re-Training Framework Based on the Adaboost Algorithm .

Degree: 2015, University of Bridgeport

Object detection, such as face detection using supervised learning, often requires extensive training for the computer, which results in high execution times. If the trained… (more)

Subjects/Keywords: Computer science; Object detection

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APA (6th Edition):

Abualkibash, M. H. (2015). A Near Real-Time, Highly Scalable, Parallel and Distributed Adaptive Object Detection and Re-Training Framework Based on the Adaboost Algorithm . (Thesis). University of Bridgeport. Retrieved from https://scholarworks.bridgeport.edu/xmlui/handle/123456789/1213

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):

Abualkibash, Munther Hamad. “A Near Real-Time, Highly Scalable, Parallel and Distributed Adaptive Object Detection and Re-Training Framework Based on the Adaboost Algorithm .” 2015. Thesis, University of Bridgeport. Accessed September 19, 2019. https://scholarworks.bridgeport.edu/xmlui/handle/123456789/1213.

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

MLA Handbook (7th Edition):

Abualkibash, Munther Hamad. “A Near Real-Time, Highly Scalable, Parallel and Distributed Adaptive Object Detection and Re-Training Framework Based on the Adaboost Algorithm .” 2015. Web. 19 Sep 2019.

Vancouver:

Abualkibash MH. A Near Real-Time, Highly Scalable, Parallel and Distributed Adaptive Object Detection and Re-Training Framework Based on the Adaboost Algorithm . [Internet] [Thesis]. University of Bridgeport; 2015. [cited 2019 Sep 19]. Available from: https://scholarworks.bridgeport.edu/xmlui/handle/123456789/1213.

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

Council of Science Editors:

Abualkibash MH. A Near Real-Time, Highly Scalable, Parallel and Distributed Adaptive Object Detection and Re-Training Framework Based on the Adaboost Algorithm . [Thesis]. University of Bridgeport; 2015. Available from: https://scholarworks.bridgeport.edu/xmlui/handle/123456789/1213

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


Virginia Tech

9. Yellapantula, Sudha Ravali. Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection.

Degree: MS, Electrical and Computer Engineering, 2019, Virginia Tech

 In the thesis, we aimed at building a robust UAV(drone) detection algorithm through which, one drone could detect another drone in flight. Though this was… (more)

Subjects/Keywords: GANs; Deep Learning; Object Detection

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

APA (6th Edition):

Yellapantula, S. R. (2019). Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/91460

Chicago Manual of Style (16th Edition):

Yellapantula, Sudha Ravali. “Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection.” 2019. Masters Thesis, Virginia Tech. Accessed September 19, 2019. http://hdl.handle.net/10919/91460.

MLA Handbook (7th Edition):

Yellapantula, Sudha Ravali. “Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection.” 2019. Web. 19 Sep 2019.

Vancouver:

Yellapantula SR. Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10919/91460.

Council of Science Editors:

Yellapantula SR. Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/91460


University of Ottawa

10. Zhao, Weihong. A Novel Animal Detection Technique for Intelligent Vehicles .

Degree: 2018, University of Ottawa

 The animal-vehicle collision has been a topic of concern for years, especially in North America. To mitigate the problem, this thesis focuses on animal detection(more)

Subjects/Keywords: object detection; R-CNN; animal detection; MSER

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APA (6th Edition):

Zhao, W. (2018). A Novel Animal Detection Technique for Intelligent Vehicles . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/38045

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):

Zhao, Weihong. “A Novel Animal Detection Technique for Intelligent Vehicles .” 2018. Thesis, University of Ottawa. Accessed September 19, 2019. http://hdl.handle.net/10393/38045.

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

MLA Handbook (7th Edition):

Zhao, Weihong. “A Novel Animal Detection Technique for Intelligent Vehicles .” 2018. Web. 19 Sep 2019.

Vancouver:

Zhao W. A Novel Animal Detection Technique for Intelligent Vehicles . [Internet] [Thesis]. University of Ottawa; 2018. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10393/38045.

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

Council of Science Editors:

Zhao W. A Novel Animal Detection Technique for Intelligent Vehicles . [Thesis]. University of Ottawa; 2018. Available from: http://hdl.handle.net/10393/38045

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


Virginia Tech

11. Nguyen, Chuong Hoang. Features identification and tracking for an autonomous ground vehicle.

Degree: MS, Mechanical Engineering, 2013, Virginia Tech

 This thesis attempts to develop features identification and tracking system for an autonomous ground vehicle by focusing on four fundamental tasks: Motion detection, object tracking,… (more)

Subjects/Keywords: Motion detection; object tracking; scene recognition; object detection

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APA (6th Edition):

Nguyen, C. H. (2013). Features identification and tracking for an autonomous ground vehicle. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/33127

Chicago Manual of Style (16th Edition):

Nguyen, Chuong Hoang. “Features identification and tracking for an autonomous ground vehicle.” 2013. Masters Thesis, Virginia Tech. Accessed September 19, 2019. http://hdl.handle.net/10919/33127.

MLA Handbook (7th Edition):

Nguyen, Chuong Hoang. “Features identification and tracking for an autonomous ground vehicle.” 2013. Web. 19 Sep 2019.

Vancouver:

Nguyen CH. Features identification and tracking for an autonomous ground vehicle. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10919/33127.

Council of Science Editors:

Nguyen CH. Features identification and tracking for an autonomous ground vehicle. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/33127


Universiteit Utrecht

12. Deiman, J. Automatic Tracking, Segmentation, Removal and Replay of Traffic in Panoramic 360-Degree Videos for Virtual Reality.

Degree: 2016, Universiteit Utrecht

 The Netherlands Aerospace Centre (NLR) has a virtual reality setup which allows users to experience an airplane fly-over with realistically simulated sound. They want to… (more)

Subjects/Keywords: object detection; object tracking; object segmentation; inpainting; virtual reality; panoramic video

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

APA (6th Edition):

Deiman, J. (2016). Automatic Tracking, Segmentation, Removal and Replay of Traffic in Panoramic 360-Degree Videos for Virtual Reality. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/334268

Chicago Manual of Style (16th Edition):

Deiman, J. “Automatic Tracking, Segmentation, Removal and Replay of Traffic in Panoramic 360-Degree Videos for Virtual Reality.” 2016. Masters Thesis, Universiteit Utrecht. Accessed September 19, 2019. http://dspace.library.uu.nl:8080/handle/1874/334268.

MLA Handbook (7th Edition):

Deiman, J. “Automatic Tracking, Segmentation, Removal and Replay of Traffic in Panoramic 360-Degree Videos for Virtual Reality.” 2016. Web. 19 Sep 2019.

Vancouver:

Deiman J. Automatic Tracking, Segmentation, Removal and Replay of Traffic in Panoramic 360-Degree Videos for Virtual Reality. [Internet] [Masters thesis]. Universiteit Utrecht; 2016. [cited 2019 Sep 19]. Available from: http://dspace.library.uu.nl:8080/handle/1874/334268.

Council of Science Editors:

Deiman J. Automatic Tracking, Segmentation, Removal and Replay of Traffic in Panoramic 360-Degree Videos for Virtual Reality. [Masters Thesis]. Universiteit Utrecht; 2016. Available from: http://dspace.library.uu.nl:8080/handle/1874/334268


Linköping University

13. Nyström, Axel. Evaluation of Multiple Object Tracking in Surveillance Video.

Degree: Computer Vision, 2019, Linköping University

  Multiple object tracking is the process of assigning unique and consistent identities to objects throughout a video sequence. A popular approach to multiple object(more)

Subjects/Keywords: Multiple Object Tracking; Tracking-by-Detection; Object Detection; Object Tracking; Deep Learning; Signal Processing; Signalbehandling

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

APA (6th Edition):

Nyström, A. (2019). Evaluation of Multiple Object Tracking in Surveillance Video. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666

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):

Nyström, Axel. “Evaluation of Multiple Object Tracking in Surveillance Video.” 2019. Thesis, Linköping University. Accessed September 19, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666.

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

MLA Handbook (7th Edition):

Nyström, Axel. “Evaluation of Multiple Object Tracking in Surveillance Video.” 2019. Web. 19 Sep 2019.

Vancouver:

Nyström A. Evaluation of Multiple Object Tracking in Surveillance Video. [Internet] [Thesis]. Linköping University; 2019. [cited 2019 Sep 19]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666.

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

Council of Science Editors:

Nyström A. Evaluation of Multiple Object Tracking in Surveillance Video. [Thesis]. Linköping University; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666

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


Australian National University

14. Zhang, Haoyang. Learning to Generate and Refine Object Proposals .

Degree: 2018, Australian National University

 Visual object recognition is a fundamental and challenging problem in computer vision. To build a practical recognition system, one is first confronted with high computation… (more)

Subjects/Keywords: object proposal; object candidate; object detection; object instance segmentation; convolutional neural network (CNN)

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APA (6th Edition):

Zhang, H. (2018). Learning to Generate and Refine Object Proposals . (Thesis). Australian National University. Retrieved from http://hdl.handle.net/1885/143520

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):

Zhang, Haoyang. “Learning to Generate and Refine Object Proposals .” 2018. Thesis, Australian National University. Accessed September 19, 2019. http://hdl.handle.net/1885/143520.

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

MLA Handbook (7th Edition):

Zhang, Haoyang. “Learning to Generate and Refine Object Proposals .” 2018. Web. 19 Sep 2019.

Vancouver:

Zhang H. Learning to Generate and Refine Object Proposals . [Internet] [Thesis]. Australian National University; 2018. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/1885/143520.

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

Council of Science Editors:

Zhang H. Learning to Generate and Refine Object Proposals . [Thesis]. Australian National University; 2018. Available from: http://hdl.handle.net/1885/143520

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


NSYSU

15. Liu, Jia-Ying. Real-time Face Recognition System with Self-learning.

Degree: Master, Computer Science and Engineering, 2017, NSYSU

 Face recognition has matured over the recent years, it is widely used in access control system, immigration control system even lecture attendance system. Traditional face… (more)

Subjects/Keywords: Face recognition; Face detection; Skin color detection; Moving object detection; Object tracking

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APA (6th Edition):

Liu, J. (2017). Real-time Face Recognition System with Self-learning. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0426117-093435

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):

Liu, Jia-Ying. “Real-time Face Recognition System with Self-learning.” 2017. Thesis, NSYSU. Accessed September 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0426117-093435.

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

MLA Handbook (7th Edition):

Liu, Jia-Ying. “Real-time Face Recognition System with Self-learning.” 2017. Web. 19 Sep 2019.

Vancouver:

Liu J. Real-time Face Recognition System with Self-learning. [Internet] [Thesis]. NSYSU; 2017. [cited 2019 Sep 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0426117-093435.

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

Council of Science Editors:

Liu J. Real-time Face Recognition System with Self-learning. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0426117-093435

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


University of Adelaide

16. Cao, Yuanzhouhan. Deep learning based RGB-D vision tasks.

Degree: 2018, University of Adelaide

 Depth is an important source of information in computer vision. However, depth is usually discarded in most vision tasks. In this thesis, we study the… (more)

Subjects/Keywords: depth estimation; object detection; semantic segmentation

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

APA (6th Edition):

Cao, Y. (2018). Deep learning based RGB-D vision tasks. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/112866

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):

Cao, Yuanzhouhan. “Deep learning based RGB-D vision tasks.” 2018. Thesis, University of Adelaide. Accessed September 19, 2019. http://hdl.handle.net/2440/112866.

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

MLA Handbook (7th Edition):

Cao, Yuanzhouhan. “Deep learning based RGB-D vision tasks.” 2018. Web. 19 Sep 2019.

Vancouver:

Cao Y. Deep learning based RGB-D vision tasks. [Internet] [Thesis]. University of Adelaide; 2018. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/2440/112866.

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

Council of Science Editors:

Cao Y. Deep learning based RGB-D vision tasks. [Thesis]. University of Adelaide; 2018. Available from: http://hdl.handle.net/2440/112866

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


King Abdullah University of Science and Technology

17. Alharbi, Yazeed. Marker Detection in Aerial Images.

Degree: 2017, King Abdullah University of Science and Technology

 The problem that the thesis is trying to solve is the detection of small markers in high-resolution aerial images. Given a high-resolution image, the goal… (more)

Subjects/Keywords: vision; computer; detection; tracking; object; description

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

APA (6th Edition):

Alharbi, Y. (2017). Marker Detection in Aerial Images. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/623123

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):

Alharbi, Yazeed. “Marker Detection in Aerial Images.” 2017. Thesis, King Abdullah University of Science and Technology. Accessed September 19, 2019. http://hdl.handle.net/10754/623123.

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

MLA Handbook (7th Edition):

Alharbi, Yazeed. “Marker Detection in Aerial Images.” 2017. Web. 19 Sep 2019.

Vancouver:

Alharbi Y. Marker Detection in Aerial Images. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2017. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10754/623123.

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

Council of Science Editors:

Alharbi Y. Marker Detection in Aerial Images. [Thesis]. King Abdullah University of Science and Technology; 2017. Available from: http://hdl.handle.net/10754/623123

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


King Abdullah University of Science and Technology

18. Lao, Dong. Minimum Delay Moving Object Detection.

Degree: 2017, King Abdullah University of Science and Technology

 This thesis presents a general framework and method for detection of an object in a video based on apparent motion. The object moves, at some… (more)

Subjects/Keywords: object detection; motion segmentation; optimal delay

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

APA (6th Edition):

Lao, D. (2017). Minimum Delay Moving Object Detection. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/623619

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):

Lao, Dong. “Minimum Delay Moving Object Detection.” 2017. Thesis, King Abdullah University of Science and Technology. Accessed September 19, 2019. http://hdl.handle.net/10754/623619.

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

MLA Handbook (7th Edition):

Lao, Dong. “Minimum Delay Moving Object Detection.” 2017. Web. 19 Sep 2019.

Vancouver:

Lao D. Minimum Delay Moving Object Detection. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2017. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10754/623619.

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

Council of Science Editors:

Lao D. Minimum Delay Moving Object Detection. [Thesis]. King Abdullah University of Science and Technology; 2017. Available from: http://hdl.handle.net/10754/623619

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


University of Ottawa

19. Wang, Binghao. Object Detection with Two-stream Convolutional Networks and Scene Geometry Information .

Degree: 2019, University of Ottawa

 With the emergence of Convolutional Neural Network (CNN) models, precision of image classification tasks has been improved significantly over these years. Regional CNN (RCNN) model… (more)

Subjects/Keywords: object detection; two-stream convolutional network

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

APA (6th Edition):

Wang, B. (2019). Object Detection with Two-stream Convolutional Networks and Scene Geometry Information . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/38873

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):

Wang, Binghao. “Object Detection with Two-stream Convolutional Networks and Scene Geometry Information .” 2019. Thesis, University of Ottawa. Accessed September 19, 2019. http://hdl.handle.net/10393/38873.

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

MLA Handbook (7th Edition):

Wang, Binghao. “Object Detection with Two-stream Convolutional Networks and Scene Geometry Information .” 2019. Web. 19 Sep 2019.

Vancouver:

Wang B. Object Detection with Two-stream Convolutional Networks and Scene Geometry Information . [Internet] [Thesis]. University of Ottawa; 2019. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10393/38873.

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

Council of Science Editors:

Wang B. Object Detection with Two-stream Convolutional Networks and Scene Geometry Information . [Thesis]. University of Ottawa; 2019. Available from: http://hdl.handle.net/10393/38873

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


Texas A&M University

20. Venugopal, Lakshmi. Real-Time Detection of Foreground in Video Surveillance Cameras Using CUDA.

Degree: MS, Electrical Engineering, 2018, Texas A&M University

 The rapid growth of video processing techniques has led to remarkable contributions in several applications such as compression, filtering, segmentation and object tracking. A fundamental… (more)

Subjects/Keywords: Moving object detection; GPU; CUDA; OpenCV

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

APA (6th Edition):

Venugopal, L. (2018). Real-Time Detection of Foreground in Video Surveillance Cameras Using CUDA. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173600

Chicago Manual of Style (16th Edition):

Venugopal, Lakshmi. “Real-Time Detection of Foreground in Video Surveillance Cameras Using CUDA.” 2018. Masters Thesis, Texas A&M University. Accessed September 19, 2019. http://hdl.handle.net/1969.1/173600.

MLA Handbook (7th Edition):

Venugopal, Lakshmi. “Real-Time Detection of Foreground in Video Surveillance Cameras Using CUDA.” 2018. Web. 19 Sep 2019.

Vancouver:

Venugopal L. Real-Time Detection of Foreground in Video Surveillance Cameras Using CUDA. [Internet] [Masters thesis]. Texas A&M University; 2018. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/1969.1/173600.

Council of Science Editors:

Venugopal L. Real-Time Detection of Foreground in Video Surveillance Cameras Using CUDA. [Masters Thesis]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/173600


Victoria University of Wellington

21. Rahman, Ibrahim Mohammad Hussain. Visual attention strategies for target object detection.

Degree: 2018, Victoria University of Wellington

 The human visual attention system (HVA) encompasses a set of interconnected neurological modules that are responsible for analyzing visual stimuli by attending to those regions… (more)

Subjects/Keywords: Attention; Object detection; Saliency; Active vision

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APA (6th Edition):

Rahman, I. M. H. (2018). Visual attention strategies for target object detection. (Doctoral Dissertation). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/6925

Chicago Manual of Style (16th Edition):

Rahman, Ibrahim Mohammad Hussain. “Visual attention strategies for target object detection.” 2018. Doctoral Dissertation, Victoria University of Wellington. Accessed September 19, 2019. http://hdl.handle.net/10063/6925.

MLA Handbook (7th Edition):

Rahman, Ibrahim Mohammad Hussain. “Visual attention strategies for target object detection.” 2018. Web. 19 Sep 2019.

Vancouver:

Rahman IMH. Visual attention strategies for target object detection. [Internet] [Doctoral dissertation]. Victoria University of Wellington; 2018. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10063/6925.

Council of Science Editors:

Rahman IMH. Visual attention strategies for target object detection. [Doctoral Dissertation]. Victoria University of Wellington; 2018. Available from: http://hdl.handle.net/10063/6925


University of Waterloo

22. Mozifian, Melissa Farinaz. Real-time 3D Object Detection for Autonomous Driving.

Degree: 2018, University of Waterloo

 This thesis focuses on advancing the state-of-the-art 3D object detection and localization in autonomous driving. An autonomous vehicle requires operating within a very unpredictable and… (more)

Subjects/Keywords: Computer Vision; Object Detection; Deep Learning

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APA (6th Edition):

Mozifian, M. F. (2018). Real-time 3D Object Detection for Autonomous Driving. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13267

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):

Mozifian, Melissa Farinaz. “Real-time 3D Object Detection for Autonomous Driving.” 2018. Thesis, University of Waterloo. Accessed September 19, 2019. http://hdl.handle.net/10012/13267.

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

MLA Handbook (7th Edition):

Mozifian, Melissa Farinaz. “Real-time 3D Object Detection for Autonomous Driving.” 2018. Web. 19 Sep 2019.

Vancouver:

Mozifian MF. Real-time 3D Object Detection for Autonomous Driving. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10012/13267.

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

Council of Science Editors:

Mozifian MF. Real-time 3D Object Detection for Autonomous Driving. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13267

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


University of Toronto

23. Lo, Charles. A High-performance Architecture for Training Viola-Jones Object Detectors.

Degree: 2012, University of Toronto

The object detection framework developed by Viola and Jones has become very popular due to its high quality and detection speed. However, the complexity of… (more)

Subjects/Keywords: FPGA; Object Detection; Reconfigurable Architecture; 0544; 0800

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APA (6th Edition):

Lo, C. (2012). A High-performance Architecture for Training Viola-Jones Object Detectors. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/33294

Chicago Manual of Style (16th Edition):

Lo, Charles. “A High-performance Architecture for Training Viola-Jones Object Detectors.” 2012. Masters Thesis, University of Toronto. Accessed September 19, 2019. http://hdl.handle.net/1807/33294.

MLA Handbook (7th Edition):

Lo, Charles. “A High-performance Architecture for Training Viola-Jones Object Detectors.” 2012. Web. 19 Sep 2019.

Vancouver:

Lo C. A High-performance Architecture for Training Viola-Jones Object Detectors. [Internet] [Masters thesis]. University of Toronto; 2012. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/1807/33294.

Council of Science Editors:

Lo C. A High-performance Architecture for Training Viola-Jones Object Detectors. [Masters Thesis]. University of Toronto; 2012. Available from: http://hdl.handle.net/1807/33294


University of Toronto

24. Yoon, Juny David. Model-free Setting-independent Detection of Dynamic Objects in 3D Lidar.

Degree: 2019, University of Toronto

This thesis presents a model-free, setting-independent method for online detection of dynamic objects in 3D lidar data. We focus on a common type of 3D… (more)

Subjects/Keywords: Lidar; Lidar Odometry; Object Detection; 0771

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APA (6th Edition):

Yoon, J. D. (2019). Model-free Setting-independent Detection of Dynamic Objects in 3D Lidar. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/94034

Chicago Manual of Style (16th Edition):

Yoon, Juny David. “Model-free Setting-independent Detection of Dynamic Objects in 3D Lidar.” 2019. Masters Thesis, University of Toronto. Accessed September 19, 2019. http://hdl.handle.net/1807/94034.

MLA Handbook (7th Edition):

Yoon, Juny David. “Model-free Setting-independent Detection of Dynamic Objects in 3D Lidar.” 2019. Web. 19 Sep 2019.

Vancouver:

Yoon JD. Model-free Setting-independent Detection of Dynamic Objects in 3D Lidar. [Internet] [Masters thesis]. University of Toronto; 2019. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/1807/94034.

Council of Science Editors:

Yoon JD. Model-free Setting-independent Detection of Dynamic Objects in 3D Lidar. [Masters Thesis]. University of Toronto; 2019. Available from: http://hdl.handle.net/1807/94034


Rochester Institute of Technology

25. Harvey, Jesse Patrick. GPU acceleration of object classification algorithms using NVIDIA CUDA.

Degree: Computer Engineering, 2009, Rochester Institute of Technology

 The field of computer vision has become an important part of today's society, supporting crucial applications in the medical, manufacturing, military intelligence and surveillance domains.… (more)

Subjects/Keywords: Machine vision; Object detection; Parallel programming

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APA (6th Edition):

Harvey, J. P. (2009). GPU acceleration of object classification algorithms using NVIDIA CUDA. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/3224

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):

Harvey, Jesse Patrick. “GPU acceleration of object classification algorithms using NVIDIA CUDA.” 2009. Thesis, Rochester Institute of Technology. Accessed September 19, 2019. https://scholarworks.rit.edu/theses/3224.

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

MLA Handbook (7th Edition):

Harvey, Jesse Patrick. “GPU acceleration of object classification algorithms using NVIDIA CUDA.” 2009. Web. 19 Sep 2019.

Vancouver:

Harvey JP. GPU acceleration of object classification algorithms using NVIDIA CUDA. [Internet] [Thesis]. Rochester Institute of Technology; 2009. [cited 2019 Sep 19]. Available from: https://scholarworks.rit.edu/theses/3224.

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

Council of Science Editors:

Harvey JP. GPU acceleration of object classification algorithms using NVIDIA CUDA. [Thesis]. Rochester Institute of Technology; 2009. Available from: https://scholarworks.rit.edu/theses/3224

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


Rochester Institute of Technology

26. Case, Isaac. Automatic object detection and tracking in video.

Degree: Computer Science (GCCIS), 2010, Rochester Institute of Technology

 One ability of the human visual system is the ability to identify and track moving objects. Examples of this can easily be seen in any… (more)

Subjects/Keywords: Computer vision; Motion tracking; Object detection

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APA (6th Edition):

Case, I. (2010). Automatic object detection and tracking in video. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/244

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):

Case, Isaac. “Automatic object detection and tracking in video.” 2010. Thesis, Rochester Institute of Technology. Accessed September 19, 2019. https://scholarworks.rit.edu/theses/244.

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

MLA Handbook (7th Edition):

Case, Isaac. “Automatic object detection and tracking in video.” 2010. Web. 19 Sep 2019.

Vancouver:

Case I. Automatic object detection and tracking in video. [Internet] [Thesis]. Rochester Institute of Technology; 2010. [cited 2019 Sep 19]. Available from: https://scholarworks.rit.edu/theses/244.

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

Council of Science Editors:

Case I. Automatic object detection and tracking in video. [Thesis]. Rochester Institute of Technology; 2010. Available from: https://scholarworks.rit.edu/theses/244

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


University of Manitoba

27. Gaudreau, Colin. Fast detection of bees using deep learning and bayesian optimization.

Degree: Electrical and Computer Engineering, 2018, University of Manitoba

 In commercial beekeeping, monitoring the apiaries is difficult as they are often spread over large distances. Building a vision-based hive monitoring system is a promising—albeit… (more)

Subjects/Keywords: Computer vision; Object detection; Machine learning; Bees

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

APA (6th Edition):

Gaudreau, C. (2018). Fast detection of bees using deep learning and bayesian optimization. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/32981

Chicago Manual of Style (16th Edition):

Gaudreau, Colin. “Fast detection of bees using deep learning and bayesian optimization.” 2018. Masters Thesis, University of Manitoba. Accessed September 19, 2019. http://hdl.handle.net/1993/32981.

MLA Handbook (7th Edition):

Gaudreau, Colin. “Fast detection of bees using deep learning and bayesian optimization.” 2018. Web. 19 Sep 2019.

Vancouver:

Gaudreau C. Fast detection of bees using deep learning and bayesian optimization. [Internet] [Masters thesis]. University of Manitoba; 2018. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/1993/32981.

Council of Science Editors:

Gaudreau C. Fast detection of bees using deep learning and bayesian optimization. [Masters Thesis]. University of Manitoba; 2018. Available from: http://hdl.handle.net/1993/32981


King Abdullah University of Science and Technology

28. Xu, Mengmeng. Object Detection Using Multiple Level Annotations.

Degree: 2019, King Abdullah University of Science and Technology

Object detection is a fundamental problem in computer vision. Impressive results have been achieved on large-scale detection benchmarks by fully-supervised object detection (FSOD) methods. However,… (more)

Subjects/Keywords: Object Detection; Hybrid Supervised Learning; Training Budget

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

APA (6th Edition):

Xu, M. (2019). Object Detection Using Multiple Level Annotations. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/631958

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):

Xu, Mengmeng. “Object Detection Using Multiple Level Annotations.” 2019. Thesis, King Abdullah University of Science and Technology. Accessed September 19, 2019. http://hdl.handle.net/10754/631958.

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

MLA Handbook (7th Edition):

Xu, Mengmeng. “Object Detection Using Multiple Level Annotations.” 2019. Web. 19 Sep 2019.

Vancouver:

Xu M. Object Detection Using Multiple Level Annotations. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2019. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10754/631958.

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

Council of Science Editors:

Xu M. Object Detection Using Multiple Level Annotations. [Thesis]. King Abdullah University of Science and Technology; 2019. Available from: http://hdl.handle.net/10754/631958

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


NSYSU

29. Muchtar, Kahlil. Background Modeling with Applications in Video Surveillance Systems.

Degree: PhD, Electrical Engineering, 2017, NSYSU

 Video Surveillance has been a very active research topic in recent years. This is because the growing needs in many applications, such as object recognition,… (more)

Subjects/Keywords: background modeling; Markov Random Field; abandoned object detection; mixture of Gaussians; Moving object detection

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

APA (6th Edition):

Muchtar, K. (2017). Background Modeling with Applications in Video Surveillance Systems. (Doctoral Dissertation). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0405117-193911

Chicago Manual of Style (16th Edition):

Muchtar, Kahlil. “Background Modeling with Applications in Video Surveillance Systems.” 2017. Doctoral Dissertation, NSYSU. Accessed September 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0405117-193911.

MLA Handbook (7th Edition):

Muchtar, Kahlil. “Background Modeling with Applications in Video Surveillance Systems.” 2017. Web. 19 Sep 2019.

Vancouver:

Muchtar K. Background Modeling with Applications in Video Surveillance Systems. [Internet] [Doctoral dissertation]. NSYSU; 2017. [cited 2019 Sep 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0405117-193911.

Council of Science Editors:

Muchtar K. Background Modeling with Applications in Video Surveillance Systems. [Doctoral Dissertation]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0405117-193911


University of Edinburgh

30. Gonzalez-Garcia, Abel. Image context for object detection, object context for part detection.

Degree: PhD, 2018, University of Edinburgh

 Objects and parts are crucial elements for achieving automatic image understanding. The goal of the object detection task is to recognize and localize all the… (more)

Subjects/Keywords: object detection; automatic image; object class detection; window classifiers; convolutional neural networks

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

APA (6th Edition):

Gonzalez-Garcia, A. (2018). Image context for object detection, object context for part detection. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/28842

Chicago Manual of Style (16th Edition):

Gonzalez-Garcia, Abel. “Image context for object detection, object context for part detection.” 2018. Doctoral Dissertation, University of Edinburgh. Accessed September 19, 2019. http://hdl.handle.net/1842/28842.

MLA Handbook (7th Edition):

Gonzalez-Garcia, Abel. “Image context for object detection, object context for part detection.” 2018. Web. 19 Sep 2019.

Vancouver:

Gonzalez-Garcia A. Image context for object detection, object context for part detection. [Internet] [Doctoral dissertation]. University of Edinburgh; 2018. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/1842/28842.

Council of Science Editors:

Gonzalez-Garcia A. Image context for object detection, object context for part detection. [Doctoral Dissertation]. University of Edinburgh; 2018. Available from: http://hdl.handle.net/1842/28842

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