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You searched for subject:(cnn). Showing records 1 – 30 of 382 total matches.

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Texas A&M University

1. Song, Jianfeng. HEVC Fast CU Decision for Intra-Prediction by CNN.

Degree: MS, Electrical Engineering, 2019, Texas A&M University

 High Efficiency Video Coding (HEVC) is also know as H.265 was first official introduced in 2013, it is one of the video coding standard of… (more)

Subjects/Keywords: HEVC; CNN

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APA (6th Edition):

Song, J. (2019). HEVC Fast CU Decision for Intra-Prediction by CNN. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/188802

Chicago Manual of Style (16th Edition):

Song, Jianfeng. “HEVC Fast CU Decision for Intra-Prediction by CNN.” 2019. Masters Thesis, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/188802.

MLA Handbook (7th Edition):

Song, Jianfeng. “HEVC Fast CU Decision for Intra-Prediction by CNN.” 2019. Web. 27 Sep 2020.

Vancouver:

Song J. HEVC Fast CU Decision for Intra-Prediction by CNN. [Internet] [Masters thesis]. Texas A&M University; 2019. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/188802.

Council of Science Editors:

Song J. HEVC Fast CU Decision for Intra-Prediction by CNN. [Masters Thesis]. Texas A&M University; 2019. Available from: http://hdl.handle.net/1969.1/188802


University of Ottawa

2. Gu, Dongfeng. 3D Densely Connected Convolutional Network for the Recognition of Human Shopping Actions .

Degree: 2017, University of Ottawa

 In recent years, deep convolutional neural networks (CNNs) have shown remarkable results in the image domain. However, most of the neural networks in action recognition… (more)

Subjects/Keywords: 3D-DenseNet; CNN

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APA (6th Edition):

Gu, D. (2017). 3D Densely Connected Convolutional Network for the Recognition of Human Shopping Actions . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/36739

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):

Gu, Dongfeng. “3D Densely Connected Convolutional Network for the Recognition of Human Shopping Actions .” 2017. Thesis, University of Ottawa. Accessed September 27, 2020. http://hdl.handle.net/10393/36739.

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

MLA Handbook (7th Edition):

Gu, Dongfeng. “3D Densely Connected Convolutional Network for the Recognition of Human Shopping Actions .” 2017. Web. 27 Sep 2020.

Vancouver:

Gu D. 3D Densely Connected Convolutional Network for the Recognition of Human Shopping Actions . [Internet] [Thesis]. University of Ottawa; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10393/36739.

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

Council of Science Editors:

Gu D. 3D Densely Connected Convolutional Network for the Recognition of Human Shopping Actions . [Thesis]. University of Ottawa; 2017. Available from: http://hdl.handle.net/10393/36739

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

3. Chen, Tairui. Going Deeper with Convolutional Neural Network for Intelligent Transportation.

Degree: ME, 2016, Worcester Polytechnic Institute

 Over last several decades, computer vision researchers have been devoted to find good feature to solve different tasks, object recognition, object detection, object segmentation, activity… (more)

Subjects/Keywords: deep learning; cnn

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APA (6th Edition):

Chen, T. (2016). Going Deeper with Convolutional Neural Network for Intelligent Transportation. (Thesis). Worcester Polytechnic Institute. Retrieved from etd-012816-212024 ; https://digitalcommons.wpi.edu/etd-theses/144

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):

Chen, Tairui. “Going Deeper with Convolutional Neural Network for Intelligent Transportation.” 2016. Thesis, Worcester Polytechnic Institute. Accessed September 27, 2020. etd-012816-212024 ; https://digitalcommons.wpi.edu/etd-theses/144.

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

MLA Handbook (7th Edition):

Chen, Tairui. “Going Deeper with Convolutional Neural Network for Intelligent Transportation.” 2016. Web. 27 Sep 2020.

Vancouver:

Chen T. Going Deeper with Convolutional Neural Network for Intelligent Transportation. [Internet] [Thesis]. Worcester Polytechnic Institute; 2016. [cited 2020 Sep 27]. Available from: etd-012816-212024 ; https://digitalcommons.wpi.edu/etd-theses/144.

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

Council of Science Editors:

Chen T. Going Deeper with Convolutional Neural Network for Intelligent Transportation. [Thesis]. Worcester Polytechnic Institute; 2016. Available from: etd-012816-212024 ; https://digitalcommons.wpi.edu/etd-theses/144

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


Penn State University

4. Wang, Hang. Parsimonious Model Selection Based on Bayesian Information Criterion and a Mixture-based Hybrid Model on Image Classification.

Degree: 2019, Penn State University

 My thesis research contains two parts of work. The first part of my work revisits a previous paper about Parsimonious Topic Model, and modifies the… (more)

Subjects/Keywords: Mixture Model; Transfer Learning; CNN

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APA (6th Edition):

Wang, H. (2019). Parsimonious Model Selection Based on Bayesian Information Criterion and a Mixture-based Hybrid Model on Image Classification. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/16555hzw81

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, Hang. “Parsimonious Model Selection Based on Bayesian Information Criterion and a Mixture-based Hybrid Model on Image Classification.” 2019. Thesis, Penn State University. Accessed September 27, 2020. https://submit-etda.libraries.psu.edu/catalog/16555hzw81.

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

MLA Handbook (7th Edition):

Wang, Hang. “Parsimonious Model Selection Based on Bayesian Information Criterion and a Mixture-based Hybrid Model on Image Classification.” 2019. Web. 27 Sep 2020.

Vancouver:

Wang H. Parsimonious Model Selection Based on Bayesian Information Criterion and a Mixture-based Hybrid Model on Image Classification. [Internet] [Thesis]. Penn State University; 2019. [cited 2020 Sep 27]. Available from: https://submit-etda.libraries.psu.edu/catalog/16555hzw81.

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

Council of Science Editors:

Wang H. Parsimonious Model Selection Based on Bayesian Information Criterion and a Mixture-based Hybrid Model on Image Classification. [Thesis]. Penn State University; 2019. Available from: https://submit-etda.libraries.psu.edu/catalog/16555hzw81

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


University of Ottawa

5. Li, Xile. Real-time Multi-face Tracking with Labels based on Convolutional Neural Networks .

Degree: 2017, University of Ottawa

 This thesis presents a real-time multi-face tracking system, which is able to track multiple faces for live videos, broadcast, real-time conference recording, etc. The real-time… (more)

Subjects/Keywords: Multi-face tracking; CNN

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APA (6th Edition):

Li, X. (2017). Real-time Multi-face Tracking with Labels based on Convolutional Neural Networks . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/36707

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):

Li, Xile. “Real-time Multi-face Tracking with Labels based on Convolutional Neural Networks .” 2017. Thesis, University of Ottawa. Accessed September 27, 2020. http://hdl.handle.net/10393/36707.

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

MLA Handbook (7th Edition):

Li, Xile. “Real-time Multi-face Tracking with Labels based on Convolutional Neural Networks .” 2017. Web. 27 Sep 2020.

Vancouver:

Li X. Real-time Multi-face Tracking with Labels based on Convolutional Neural Networks . [Internet] [Thesis]. University of Ottawa; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10393/36707.

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

Council of Science Editors:

Li X. Real-time Multi-face Tracking with Labels based on Convolutional Neural Networks . [Thesis]. University of Ottawa; 2017. Available from: http://hdl.handle.net/10393/36707

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


Texas State University – San Marcos

6. Chen, Xinbo. Energy Efficiency Analysis and Optimization of Convolutional Neural Networks For Image Recognition.

Degree: MS, Computer Science, 2016, Texas State University – San Marcos

 In recent years, convolutional neural network (CNN) has been widely used to improve the training time and accuracy of image recognition applications. These CNNs are… (more)

Subjects/Keywords: Neural network; CNN; Energy efficiency

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

APA (6th Edition):

Chen, X. (2016). Energy Efficiency Analysis and Optimization of Convolutional Neural Networks For Image Recognition. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/6853

Chicago Manual of Style (16th Edition):

Chen, Xinbo. “Energy Efficiency Analysis and Optimization of Convolutional Neural Networks For Image Recognition.” 2016. Masters Thesis, Texas State University – San Marcos. Accessed September 27, 2020. https://digital.library.txstate.edu/handle/10877/6853.

MLA Handbook (7th Edition):

Chen, Xinbo. “Energy Efficiency Analysis and Optimization of Convolutional Neural Networks For Image Recognition.” 2016. Web. 27 Sep 2020.

Vancouver:

Chen X. Energy Efficiency Analysis and Optimization of Convolutional Neural Networks For Image Recognition. [Internet] [Masters thesis]. Texas State University – San Marcos; 2016. [cited 2020 Sep 27]. Available from: https://digital.library.txstate.edu/handle/10877/6853.

Council of Science Editors:

Chen X. Energy Efficiency Analysis and Optimization of Convolutional Neural Networks For Image Recognition. [Masters Thesis]. Texas State University – San Marcos; 2016. Available from: https://digital.library.txstate.edu/handle/10877/6853


Rutgers University

7. Jin, Tian, 1991-. From photos to 3D design: a product shape family design and modeling framework with image-based reconstruction and 3D convolutional neural networks.

Degree: PhD, Mechanical and Aerospace Engineering, 2019, Rutgers University

 Current development of new product and product variation is largely driven by the increasingly sophisticated and demanding customers, and product variety plays a crucial role… (more)

Subjects/Keywords: 3D-CNN; Three-dimensional imaging

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APA (6th Edition):

Jin, Tian, 1. (2019). From photos to 3D design: a product shape family design and modeling framework with image-based reconstruction and 3D convolutional neural networks. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/61772/

Chicago Manual of Style (16th Edition):

Jin, Tian, 1991-. “From photos to 3D design: a product shape family design and modeling framework with image-based reconstruction and 3D convolutional neural networks.” 2019. Doctoral Dissertation, Rutgers University. Accessed September 27, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/61772/.

MLA Handbook (7th Edition):

Jin, Tian, 1991-. “From photos to 3D design: a product shape family design and modeling framework with image-based reconstruction and 3D convolutional neural networks.” 2019. Web. 27 Sep 2020.

Vancouver:

Jin, Tian 1. From photos to 3D design: a product shape family design and modeling framework with image-based reconstruction and 3D convolutional neural networks. [Internet] [Doctoral dissertation]. Rutgers University; 2019. [cited 2020 Sep 27]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/61772/.

Council of Science Editors:

Jin, Tian 1. From photos to 3D design: a product shape family design and modeling framework with image-based reconstruction and 3D convolutional neural networks. [Doctoral Dissertation]. Rutgers University; 2019. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/61772/


University of Arizona

8. Guo, Jiashu. Deep Neural Networks for Modeling Sequential Prediction Tasks with Applications in Brain Tumors .

Degree: 2018, University of Arizona

 Gliomas are malignant brain tumors that are associated with high neurological morbidity and poor outcomes. Patients diagnosed with low-grade gliomas are typically followed by a… (more)

Subjects/Keywords: CNN; Gliomas; LSTM; Sequential

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APA (6th Edition):

Guo, J. (2018). Deep Neural Networks for Modeling Sequential Prediction Tasks with Applications in Brain Tumors . (Masters Thesis). University of Arizona. Retrieved from http://hdl.handle.net/10150/630148

Chicago Manual of Style (16th Edition):

Guo, Jiashu. “Deep Neural Networks for Modeling Sequential Prediction Tasks with Applications in Brain Tumors .” 2018. Masters Thesis, University of Arizona. Accessed September 27, 2020. http://hdl.handle.net/10150/630148.

MLA Handbook (7th Edition):

Guo, Jiashu. “Deep Neural Networks for Modeling Sequential Prediction Tasks with Applications in Brain Tumors .” 2018. Web. 27 Sep 2020.

Vancouver:

Guo J. Deep Neural Networks for Modeling Sequential Prediction Tasks with Applications in Brain Tumors . [Internet] [Masters thesis]. University of Arizona; 2018. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10150/630148.

Council of Science Editors:

Guo J. Deep Neural Networks for Modeling Sequential Prediction Tasks with Applications in Brain Tumors . [Masters Thesis]. University of Arizona; 2018. Available from: http://hdl.handle.net/10150/630148


Brno University of Technology

9. Jelínek, Zdeněk. Počítání vozidel ve statickém obraze: Vehicle Counting in Still Image.

Degree: 2020, Brno University of Technology

 The main goal of this thesis was to compare different approaches to vehicle counting by density estimation. Four convolutional neural networks were tested - Counting… (more)

Subjects/Keywords: konvoluční neuronové sítě; mapa hustoty; odhad hustoty; počítání vozidel; Counting CNN; Hydra CNN; Perspective-Aware CNN; Multi-column CNN; convolutional neural networks; density map; density estimation; vehicle counting; Counting CNN; Hydra CNN; Perspective-Aware CNN; Multi-column CNN

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APA (6th Edition):

Jelínek, Z. (2020). Počítání vozidel ve statickém obraze: Vehicle Counting in Still Image. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/191687

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):

Jelínek, Zdeněk. “Počítání vozidel ve statickém obraze: Vehicle Counting in Still Image.” 2020. Thesis, Brno University of Technology. Accessed September 27, 2020. http://hdl.handle.net/11012/191687.

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

MLA Handbook (7th Edition):

Jelínek, Zdeněk. “Počítání vozidel ve statickém obraze: Vehicle Counting in Still Image.” 2020. Web. 27 Sep 2020.

Vancouver:

Jelínek Z. Počítání vozidel ve statickém obraze: Vehicle Counting in Still Image. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/11012/191687.

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

Council of Science Editors:

Jelínek Z. Počítání vozidel ve statickém obraze: Vehicle Counting in Still Image. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/191687

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

10. Γεωργάνα, Αθηνά. Νευρωνικά δίκτυα: αρχιτεκτονική και εφαρμογές.

Degree: 2008, University of Patras

Μια σύντομη αναφορά σε κάποια γνωστά μοντέλα Νευρωνικών Δικτύων, περιγραφή της αρχιτεκτονικής τους και εφαρμογές. Παραδείγματα και εφαρμογές Δυναμικών Νευρωνικών Δικτύων. Γενικό πλαίσιο λειτουργίας των… (more)

Subjects/Keywords: Νευρωνικά δίκτυα; 006.32; Neural networks; CNN

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APA (6th Edition):

Γεωργάνα, . (2008). Νευρωνικά δίκτυα: αρχιτεκτονική και εφαρμογές. (Masters Thesis). University of Patras. Retrieved from http://nemertes.lis.upatras.gr/jspui/handle/10889/782

Chicago Manual of Style (16th Edition):

Γεωργάνα, Αθηνά. “Νευρωνικά δίκτυα: αρχιτεκτονική και εφαρμογές.” 2008. Masters Thesis, University of Patras. Accessed September 27, 2020. http://nemertes.lis.upatras.gr/jspui/handle/10889/782.

MLA Handbook (7th Edition):

Γεωργάνα, Αθηνά. “Νευρωνικά δίκτυα: αρχιτεκτονική και εφαρμογές.” 2008. Web. 27 Sep 2020.

Vancouver:

Γεωργάνα . Νευρωνικά δίκτυα: αρχιτεκτονική και εφαρμογές. [Internet] [Masters thesis]. University of Patras; 2008. [cited 2020 Sep 27]. Available from: http://nemertes.lis.upatras.gr/jspui/handle/10889/782.

Council of Science Editors:

Γεωργάνα . Νευρωνικά δίκτυα: αρχιτεκτονική και εφαρμογές. [Masters Thesis]. University of Patras; 2008. Available from: http://nemertes.lis.upatras.gr/jspui/handle/10889/782


University of Waterloo

11. Kumar, Devinder. Class Based Strategies for Understanding Neural Networks.

Degree: 2020, University of Waterloo

 One of the main challenges for broad adoption of deep learning based models such as Convolutional Neural Networks (CNN), is the lack of understanding of… (more)

Subjects/Keywords: explainable AI; interpretability; CNN; fairness; XAI

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APA (6th Edition):

Kumar, D. (2020). Class Based Strategies for Understanding Neural Networks. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15626

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):

Kumar, Devinder. “Class Based Strategies for Understanding Neural Networks.” 2020. Thesis, University of Waterloo. Accessed September 27, 2020. http://hdl.handle.net/10012/15626.

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

MLA Handbook (7th Edition):

Kumar, Devinder. “Class Based Strategies for Understanding Neural Networks.” 2020. Web. 27 Sep 2020.

Vancouver:

Kumar D. Class Based Strategies for Understanding Neural Networks. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10012/15626.

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

Council of Science Editors:

Kumar D. Class Based Strategies for Understanding Neural Networks. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15626

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

12. Nordeng, Ian Edward. Dead End Body Component Inspections With Convolutional Neural Networks Using UAS Imagery.

Degree: MS, Mechanical Engineering, 2018, University of North Dakota

  This work presents a novel system utilizing previously developed convolutional neural network (CNN) architectures to aid in automating maintenance inspections of the dead-end body… (more)

Subjects/Keywords: CNN; Convolutional Neural Network; Inspections; Machine Learning

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APA (6th Edition):

Nordeng, I. E. (2018). Dead End Body Component Inspections With Convolutional Neural Networks Using UAS Imagery. (Masters Thesis). University of North Dakota. Retrieved from https://commons.und.edu/theses/2300

Chicago Manual of Style (16th Edition):

Nordeng, Ian Edward. “Dead End Body Component Inspections With Convolutional Neural Networks Using UAS Imagery.” 2018. Masters Thesis, University of North Dakota. Accessed September 27, 2020. https://commons.und.edu/theses/2300.

MLA Handbook (7th Edition):

Nordeng, Ian Edward. “Dead End Body Component Inspections With Convolutional Neural Networks Using UAS Imagery.” 2018. Web. 27 Sep 2020.

Vancouver:

Nordeng IE. Dead End Body Component Inspections With Convolutional Neural Networks Using UAS Imagery. [Internet] [Masters thesis]. University of North Dakota; 2018. [cited 2020 Sep 27]. Available from: https://commons.und.edu/theses/2300.

Council of Science Editors:

Nordeng IE. Dead End Body Component Inspections With Convolutional Neural Networks Using UAS Imagery. [Masters Thesis]. University of North Dakota; 2018. Available from: https://commons.und.edu/theses/2300


Universiteit Utrecht

13. Ugne, T. CNN Effect: Power or Mean? Study of Media Influence on Foreign Policy Decision - MakingComparative Analysis of Two Humanitarian Disasters: Ethiopia (1984 – 1985) and Somalia (1992).

Degree: 2006, Universiteit Utrecht

The thesis analyzes media's effect on American foreign policy during humanitarian crises. While comparing two similar cases of humanitarian disaster (Ethiopian famine (1984-1985) and humanitarian intervention in Somalia (1992)) the effects of media are defined. Advisors/Committee Members: Duyvesteyn, I..

Subjects/Keywords: Letteren; CNN effect

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APA (6th Edition):

Ugne, T. (2006). CNN Effect: Power or Mean? Study of Media Influence on Foreign Policy Decision - MakingComparative Analysis of Two Humanitarian Disasters: Ethiopia (1984 – 1985) and Somalia (1992). (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/13712

Chicago Manual of Style (16th Edition):

Ugne, T. “CNN Effect: Power or Mean? Study of Media Influence on Foreign Policy Decision - MakingComparative Analysis of Two Humanitarian Disasters: Ethiopia (1984 – 1985) and Somalia (1992).” 2006. Masters Thesis, Universiteit Utrecht. Accessed September 27, 2020. http://dspace.library.uu.nl:8080/handle/1874/13712.

MLA Handbook (7th Edition):

Ugne, T. “CNN Effect: Power or Mean? Study of Media Influence on Foreign Policy Decision - MakingComparative Analysis of Two Humanitarian Disasters: Ethiopia (1984 – 1985) and Somalia (1992).” 2006. Web. 27 Sep 2020.

Vancouver:

Ugne T. CNN Effect: Power or Mean? Study of Media Influence on Foreign Policy Decision - MakingComparative Analysis of Two Humanitarian Disasters: Ethiopia (1984 – 1985) and Somalia (1992). [Internet] [Masters thesis]. Universiteit Utrecht; 2006. [cited 2020 Sep 27]. Available from: http://dspace.library.uu.nl:8080/handle/1874/13712.

Council of Science Editors:

Ugne T. CNN Effect: Power or Mean? Study of Media Influence on Foreign Policy Decision - MakingComparative Analysis of Two Humanitarian Disasters: Ethiopia (1984 – 1985) and Somalia (1992). [Masters Thesis]. Universiteit Utrecht; 2006. Available from: http://dspace.library.uu.nl:8080/handle/1874/13712


Uppsala University

14. Eklund, Anton. Cascade Mask R-CNN and Keypoint Detection used in Floorplan Parsing.

Degree: Information Technology, 2020, Uppsala University

  Parsing floorplans have been a problem in automatic document analysis for long and have up until recent years been approached with algorithmic methods. With… (more)

Subjects/Keywords: mask r-cnn; cascade r-cnn; cascade mask r-cnn; floorplan; floorplans; computer vision; CNN; convolutional neural networks; Engineering and Technology; Teknik och teknologier

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APA (6th Edition):

Eklund, A. (2020). Cascade Mask R-CNN and Keypoint Detection used in Floorplan Parsing. (Thesis). Uppsala University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-415371

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):

Eklund, Anton. “Cascade Mask R-CNN and Keypoint Detection used in Floorplan Parsing.” 2020. Thesis, Uppsala University. Accessed September 27, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-415371.

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

MLA Handbook (7th Edition):

Eklund, Anton. “Cascade Mask R-CNN and Keypoint Detection used in Floorplan Parsing.” 2020. Web. 27 Sep 2020.

Vancouver:

Eklund A. Cascade Mask R-CNN and Keypoint Detection used in Floorplan Parsing. [Internet] [Thesis]. Uppsala University; 2020. [cited 2020 Sep 27]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-415371.

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

Council of Science Editors:

Eklund A. Cascade Mask R-CNN and Keypoint Detection used in Floorplan Parsing. [Thesis]. Uppsala University; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-415371

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


University of Adelaide

15. Liao, Zhibin. Methods for Understanding and Improving Deep Learning Classification Models.

Degree: 2017, University of Adelaide

 Recently proposed deep learning systems can achieve superior performance with respect to methods based on hand-crafted features on a broad range of tasks, not limited… (more)

Subjects/Keywords: Deep learning; machine learning; classification; CNN

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

APA (6th Edition):

Liao, Z. (2017). Methods for Understanding and Improving Deep Learning Classification Models. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/119246

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):

Liao, Zhibin. “Methods for Understanding and Improving Deep Learning Classification Models.” 2017. Thesis, University of Adelaide. Accessed September 27, 2020. http://hdl.handle.net/2440/119246.

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

MLA Handbook (7th Edition):

Liao, Zhibin. “Methods for Understanding and Improving Deep Learning Classification Models.” 2017. Web. 27 Sep 2020.

Vancouver:

Liao Z. Methods for Understanding and Improving Deep Learning Classification Models. [Internet] [Thesis]. University of Adelaide; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/2440/119246.

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

Council of Science Editors:

Liao Z. Methods for Understanding and Improving Deep Learning Classification Models. [Thesis]. University of Adelaide; 2017. Available from: http://hdl.handle.net/2440/119246

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

16. Petersson, Anna. Är "no news" verkligen "good news"? : En studie av hur tre svenska webbtidningar rapporterar om fem konflikter och hur teorierna CNN-effekten och Stealth Conflicts kan förklara detta.

Degree: Faculty of Arts and Sciences, 2014, Linköping UniversityLinköping University

  Is there any truth in the saying “no news is good news” or is there a reason to question whether media actually do reflect… (more)

Subjects/Keywords: media; conflict; CNN Effect; Stealth Conflicts

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APA (6th Edition):

Petersson, A. (2014). Är "no news" verkligen "good news"? : En studie av hur tre svenska webbtidningar rapporterar om fem konflikter och hur teorierna CNN-effekten och Stealth Conflicts kan förklara detta. (Thesis). Linköping UniversityLinköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-103932

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):

Petersson, Anna. “Är "no news" verkligen "good news"? : En studie av hur tre svenska webbtidningar rapporterar om fem konflikter och hur teorierna CNN-effekten och Stealth Conflicts kan förklara detta.” 2014. Thesis, Linköping UniversityLinköping University. Accessed September 27, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-103932.

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

MLA Handbook (7th Edition):

Petersson, Anna. “Är "no news" verkligen "good news"? : En studie av hur tre svenska webbtidningar rapporterar om fem konflikter och hur teorierna CNN-effekten och Stealth Conflicts kan förklara detta.” 2014. Web. 27 Sep 2020.

Vancouver:

Petersson A. Är "no news" verkligen "good news"? : En studie av hur tre svenska webbtidningar rapporterar om fem konflikter och hur teorierna CNN-effekten och Stealth Conflicts kan förklara detta. [Internet] [Thesis]. Linköping UniversityLinköping University; 2014. [cited 2020 Sep 27]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-103932.

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

Council of Science Editors:

Petersson A. Är "no news" verkligen "good news"? : En studie av hur tre svenska webbtidningar rapporterar om fem konflikter och hur teorierna CNN-effekten och Stealth Conflicts kan förklara detta. [Thesis]. Linköping UniversityLinköping University; 2014. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-103932

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


Delft University of Technology

17. Zijlmans, Jeroen (author). Improving Monocular SLAM: using Depth Estimating CNN.

Degree: 2018, Delft University of Technology

 To bring down the number of traffic accidents and increase people’s mobility companies, such as Robot Engineering Systems (RES) try to put automated vehicles on… (more)

Subjects/Keywords: monocular SLAM; Depth-estimating CNN; ORB-SLAM

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

APA (6th Edition):

Zijlmans, J. (. (2018). Improving Monocular SLAM: using Depth Estimating CNN. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:af8aad54-e594-4cfe-a2ef-a3b3f302a4d5

Chicago Manual of Style (16th Edition):

Zijlmans, Jeroen (author). “Improving Monocular SLAM: using Depth Estimating CNN.” 2018. Masters Thesis, Delft University of Technology. Accessed September 27, 2020. http://resolver.tudelft.nl/uuid:af8aad54-e594-4cfe-a2ef-a3b3f302a4d5.

MLA Handbook (7th Edition):

Zijlmans, Jeroen (author). “Improving Monocular SLAM: using Depth Estimating CNN.” 2018. Web. 27 Sep 2020.

Vancouver:

Zijlmans J(. Improving Monocular SLAM: using Depth Estimating CNN. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Sep 27]. Available from: http://resolver.tudelft.nl/uuid:af8aad54-e594-4cfe-a2ef-a3b3f302a4d5.

Council of Science Editors:

Zijlmans J(. Improving Monocular SLAM: using Depth Estimating CNN. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:af8aad54-e594-4cfe-a2ef-a3b3f302a4d5


Delft University of Technology

18. Wen, Xiaoming (author). Learning Scale-Aware Optical Flow.

Degree: 2018, Delft University of Technology

 Optical flow is a representation of projected real-world motion of the object between two consecutive images. The optical flow measures the pixel displacement on the… (more)

Subjects/Keywords: Optica Flow; CNN; Scale-Aware; Derivative

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

APA (6th Edition):

Wen, X. (. (2018). Learning Scale-Aware Optical Flow. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:7e29ed6a-b1d8-490b-bfa0-b576e6e7887c

Chicago Manual of Style (16th Edition):

Wen, Xiaoming (author). “Learning Scale-Aware Optical Flow.” 2018. Masters Thesis, Delft University of Technology. Accessed September 27, 2020. http://resolver.tudelft.nl/uuid:7e29ed6a-b1d8-490b-bfa0-b576e6e7887c.

MLA Handbook (7th Edition):

Wen, Xiaoming (author). “Learning Scale-Aware Optical Flow.” 2018. Web. 27 Sep 2020.

Vancouver:

Wen X(. Learning Scale-Aware Optical Flow. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Sep 27]. Available from: http://resolver.tudelft.nl/uuid:7e29ed6a-b1d8-490b-bfa0-b576e6e7887c.

Council of Science Editors:

Wen X(. Learning Scale-Aware Optical Flow. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:7e29ed6a-b1d8-490b-bfa0-b576e6e7887c


NSYSU

19. Wu, Pei-Hsuan. Architecture Design and Implementation of Deep Neural Network Hardware Accelerators.

Degree: Master, Computer Science and Engineering, 2018, NSYSU

 Deep Neural Networks (DNN) widely used in computer vision applications have superior performance in image classification and object detection. However, the huge amount of data… (more)

Subjects/Keywords: CNN hardware accelerator; deep neural network (DNN); convolutional neural network (CNN); machine learning

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

APA (6th Edition):

Wu, P. (2018). Architecture Design and Implementation of Deep Neural Network Hardware Accelerators. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729118-154714

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):

Wu, Pei-Hsuan. “Architecture Design and Implementation of Deep Neural Network Hardware Accelerators.” 2018. Thesis, NSYSU. Accessed September 27, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729118-154714.

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

MLA Handbook (7th Edition):

Wu, Pei-Hsuan. “Architecture Design and Implementation of Deep Neural Network Hardware Accelerators.” 2018. Web. 27 Sep 2020.

Vancouver:

Wu P. Architecture Design and Implementation of Deep Neural Network Hardware Accelerators. [Internet] [Thesis]. NSYSU; 2018. [cited 2020 Sep 27]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729118-154714.

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

Council of Science Editors:

Wu P. Architecture Design and Implementation of Deep Neural Network Hardware Accelerators. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729118-154714

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

20. Lorrain, Vincent. Etude et conception de circuits innovants exploitant les caractéristiques des nouvelles technologies mémoires résistives : Study and design of an innovative chip leveraging the characteristics of resistive memory technologies.

Degree: Docteur es, Physique, 2018, Université Paris-Saclay (ComUE)

Dans cette thèse, nous étudions les approches calculatoires dédiées des réseaux de neurones profonds et plus particulièrement des réseaux de neurones convolutionnels (CNN). En effet,… (more)

Subjects/Keywords: Neurone; Impulsion; Cnn; Puce; FDSOI 28nm; Neuron; Spike; Cnn; Chip; FDSOI 28nm

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

APA (6th Edition):

Lorrain, V. (2018). Etude et conception de circuits innovants exploitant les caractéristiques des nouvelles technologies mémoires résistives : Study and design of an innovative chip leveraging the characteristics of resistive memory technologies. (Doctoral Dissertation). Université Paris-Saclay (ComUE). Retrieved from http://www.theses.fr/2018SACLS182

Chicago Manual of Style (16th Edition):

Lorrain, Vincent. “Etude et conception de circuits innovants exploitant les caractéristiques des nouvelles technologies mémoires résistives : Study and design of an innovative chip leveraging the characteristics of resistive memory technologies.” 2018. Doctoral Dissertation, Université Paris-Saclay (ComUE). Accessed September 27, 2020. http://www.theses.fr/2018SACLS182.

MLA Handbook (7th Edition):

Lorrain, Vincent. “Etude et conception de circuits innovants exploitant les caractéristiques des nouvelles technologies mémoires résistives : Study and design of an innovative chip leveraging the characteristics of resistive memory technologies.” 2018. Web. 27 Sep 2020.

Vancouver:

Lorrain V. Etude et conception de circuits innovants exploitant les caractéristiques des nouvelles technologies mémoires résistives : Study and design of an innovative chip leveraging the characteristics of resistive memory technologies. [Internet] [Doctoral dissertation]. Université Paris-Saclay (ComUE); 2018. [cited 2020 Sep 27]. Available from: http://www.theses.fr/2018SACLS182.

Council of Science Editors:

Lorrain V. Etude et conception de circuits innovants exploitant les caractéristiques des nouvelles technologies mémoires résistives : Study and design of an innovative chip leveraging the characteristics of resistive memory technologies. [Doctoral Dissertation]. Université Paris-Saclay (ComUE); 2018. Available from: http://www.theses.fr/2018SACLS182


Brno University of Technology

21. Fischer, Martin. Detekce graffiti tagů v obraze: Detection of Graffiti Tags in Image.

Degree: 2019, Brno University of Technology

 The aim of this work is to compare different approaches of computer vision with the intention of automatic detection of graffiti tags in the image.… (more)

Subjects/Keywords: detekce objektů; graffiti tagy; konvoluční neuronové sítě; Faster R-CNN; R-FCN; Mask R-CNN; EAST detektor; CCNN; Counting CNN; object detection; graffiti tags; convolutional neural network; Faster R-CNN; R-FCN; Mask R-CNN; EAST detector; CCNN; Counting CNN

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

APA (6th Edition):

Fischer, M. (2019). Detekce graffiti tagů v obraze: Detection of Graffiti Tags in Image. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/180108

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):

Fischer, Martin. “Detekce graffiti tagů v obraze: Detection of Graffiti Tags in Image.” 2019. Thesis, Brno University of Technology. Accessed September 27, 2020. http://hdl.handle.net/11012/180108.

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

MLA Handbook (7th Edition):

Fischer, Martin. “Detekce graffiti tagů v obraze: Detection of Graffiti Tags in Image.” 2019. Web. 27 Sep 2020.

Vancouver:

Fischer M. Detekce graffiti tagů v obraze: Detection of Graffiti Tags in Image. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/11012/180108.

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

Council of Science Editors:

Fischer M. Detekce graffiti tagů v obraze: Detection of Graffiti Tags in Image. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/180108

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


University of Illinois – Urbana-Champaign

22. Li, Xing. Computer vision based corn kernel quality evaluation: Traditional versus machine learning.

Degree: MS, Electrical Engineering, 2018, University of Illinois – Urbana-Champaign

 Corn kernel quality evaluation is a trivial task for experienced farmers and agriculture researchers, but it becomes tricky if we try to develop a computer… (more)

Subjects/Keywords: Computer Vision; Corn Kernel Quality; Machine Learning; Fast R-CNN; RPN; Faster R-CNN; FPN; Retinanet.

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

APA (6th Edition):

Li, X. (2018). Computer vision based corn kernel quality evaluation: Traditional versus machine learning. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/101131

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):

Li, Xing. “Computer vision based corn kernel quality evaluation: Traditional versus machine learning.” 2018. Thesis, University of Illinois – Urbana-Champaign. Accessed September 27, 2020. http://hdl.handle.net/2142/101131.

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

MLA Handbook (7th Edition):

Li, Xing. “Computer vision based corn kernel quality evaluation: Traditional versus machine learning.” 2018. Web. 27 Sep 2020.

Vancouver:

Li X. Computer vision based corn kernel quality evaluation: Traditional versus machine learning. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2018. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/2142/101131.

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

Council of Science Editors:

Li X. Computer vision based corn kernel quality evaluation: Traditional versus machine learning. [Thesis]. University of Illinois – Urbana-Champaign; 2018. Available from: http://hdl.handle.net/2142/101131

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


Brno University of Technology

23. Dvonč, Tomáš. Automatická detekce událostí ve fotbalových zápasech: An automatic football match event detection.

Degree: 2020, Brno University of Technology

 This diploma thesis describes methods suitable for automatic detection of events from video sequences focused on football matches. The first part of the work is… (more)

Subjects/Keywords: futbal; rozpoznávanie akcie; hlboké učenie; 2D; 3D; CNN; RNN; tensorflow; football; action recognition; deep learning; 2D; 3D; CNN; RNN; tensorflow

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

APA (6th Edition):

Dvonč, T. (2020). Automatická detekce událostí ve fotbalových zápasech: An automatic football match event detection. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/189125

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):

Dvonč, Tomáš. “Automatická detekce událostí ve fotbalových zápasech: An automatic football match event detection.” 2020. Thesis, Brno University of Technology. Accessed September 27, 2020. http://hdl.handle.net/11012/189125.

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

MLA Handbook (7th Edition):

Dvonč, Tomáš. “Automatická detekce událostí ve fotbalových zápasech: An automatic football match event detection.” 2020. Web. 27 Sep 2020.

Vancouver:

Dvonč T. Automatická detekce událostí ve fotbalových zápasech: An automatic football match event detection. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/11012/189125.

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

Council of Science Editors:

Dvonč T. Automatická detekce událostí ve fotbalových zápasech: An automatic football match event detection. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/189125

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


Linköping University

24. Olin, Per. Evaluation of text classification techniques for log file classification.

Degree: Computer and Information Science, 2020, Linköping University

  System log files are filled with logged events, status codes, and other messages. By analyzing the log files, the systems current state can be… (more)

Subjects/Keywords: Text classification; machine learning; NLP; natural language processing; log file; doc2vec; CNN; LSTM; LSTM-CNN; Computer Sciences; Datavetenskap (datalogi)

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

APA (6th Edition):

Olin, P. (2020). Evaluation of text classification techniques for log file classification. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166641

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):

Olin, Per. “Evaluation of text classification techniques for log file classification.” 2020. Thesis, Linköping University. Accessed September 27, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166641.

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

MLA Handbook (7th Edition):

Olin, Per. “Evaluation of text classification techniques for log file classification.” 2020. Web. 27 Sep 2020.

Vancouver:

Olin P. Evaluation of text classification techniques for log file classification. [Internet] [Thesis]. Linköping University; 2020. [cited 2020 Sep 27]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166641.

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

Council of Science Editors:

Olin P. Evaluation of text classification techniques for log file classification. [Thesis]. Linköping University; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166641

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

25. Jacques, Céline. Méthodes d'apprentissage automatique pour la transcription automatique de la batterie : Automatic learning methods for automatic drum transcritpion.

Degree: Docteur es, Informatique, 2019, Sorbonne université

Cette thèse se concentre sur les méthodes d’apprentissage pour la transcription automatique de la batterie. Elles sont basées sur un algorithme de transcription utilisant une… (more)

Subjects/Keywords: Apprentissage; Transcription; Batterie; Apprentissage profond; CNN; NMD; Learning methods; Transcription; Drum; Deep learning; CNN; NMD; 006.31; 621.3822

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

APA (6th Edition):

Jacques, C. (2019). Méthodes d'apprentissage automatique pour la transcription automatique de la batterie : Automatic learning methods for automatic drum transcritpion. (Doctoral Dissertation). Sorbonne université. Retrieved from http://www.theses.fr/2019SORUS150

Chicago Manual of Style (16th Edition):

Jacques, Céline. “Méthodes d'apprentissage automatique pour la transcription automatique de la batterie : Automatic learning methods for automatic drum transcritpion.” 2019. Doctoral Dissertation, Sorbonne université. Accessed September 27, 2020. http://www.theses.fr/2019SORUS150.

MLA Handbook (7th Edition):

Jacques, Céline. “Méthodes d'apprentissage automatique pour la transcription automatique de la batterie : Automatic learning methods for automatic drum transcritpion.” 2019. Web. 27 Sep 2020.

Vancouver:

Jacques C. Méthodes d'apprentissage automatique pour la transcription automatique de la batterie : Automatic learning methods for automatic drum transcritpion. [Internet] [Doctoral dissertation]. Sorbonne université; 2019. [cited 2020 Sep 27]. Available from: http://www.theses.fr/2019SORUS150.

Council of Science Editors:

Jacques C. Méthodes d'apprentissage automatique pour la transcription automatique de la batterie : Automatic learning methods for automatic drum transcritpion. [Doctoral Dissertation]. Sorbonne université; 2019. Available from: http://www.theses.fr/2019SORUS150


Brno University of Technology

26. Le, Hoang Anh. Holistické rozpoznání registrační značky pomocí konvolučních neuronových sítí: Holistic License Plate Recognition Based on Convolution Neural Networks.

Degree: 2019, Brno University of Technology

 Main goal of this work was to create a holistic license plate reader, with an emphasis on achieving the highest possible accuracy on low quality… (more)

Subjects/Keywords: registrační značka; strojové učení; CNN; RNN; OCR; LSTM; CTC; license plate; machine learning; CNN; RNN; OCR; LSTM; CTC

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

APA (6th Edition):

Le, H. A. (2019). Holistické rozpoznání registrační značky pomocí konvolučních neuronových sítí: Holistic License Plate Recognition Based on Convolution Neural Networks. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/180111

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):

Le, Hoang Anh. “Holistické rozpoznání registrační značky pomocí konvolučních neuronových sítí: Holistic License Plate Recognition Based on Convolution Neural Networks.” 2019. Thesis, Brno University of Technology. Accessed September 27, 2020. http://hdl.handle.net/11012/180111.

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

MLA Handbook (7th Edition):

Le, Hoang Anh. “Holistické rozpoznání registrační značky pomocí konvolučních neuronových sítí: Holistic License Plate Recognition Based on Convolution Neural Networks.” 2019. Web. 27 Sep 2020.

Vancouver:

Le HA. Holistické rozpoznání registrační značky pomocí konvolučních neuronových sítí: Holistic License Plate Recognition Based on Convolution Neural Networks. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/11012/180111.

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

Council of Science Editors:

Le HA. Holistické rozpoznání registrační značky pomocí konvolučních neuronových sítí: Holistic License Plate Recognition Based on Convolution Neural Networks. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/180111

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


KTH

27. Norén, Gustav. Noise Robustness of Convolutional Autoencoders and Neural Networks for LPI Radar Classification.

Degree: Mathematical Statistics, 2020, KTH

This study evaluates noise robustness of convolutional autoencoders and neural networks for classification of Low Probability of Intercept (LPI) radar modulation type. Specifically, a… (more)

Subjects/Keywords: LPI radar; CNN; autoencoder; noise robustness; denoising; LPI radar; CNN; autoencoder; brustålighet; avbrusning; Probability Theory and Statistics; Sannolikhetsteori och statistik

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

APA (6th Edition):

Norén, G. (2020). Noise Robustness of Convolutional Autoencoders and Neural Networks for LPI Radar Classification. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273604

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):

Norén, Gustav. “Noise Robustness of Convolutional Autoencoders and Neural Networks for LPI Radar Classification.” 2020. Thesis, KTH. Accessed September 27, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273604.

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

MLA Handbook (7th Edition):

Norén, Gustav. “Noise Robustness of Convolutional Autoencoders and Neural Networks for LPI Radar Classification.” 2020. Web. 27 Sep 2020.

Vancouver:

Norén G. Noise Robustness of Convolutional Autoencoders and Neural Networks for LPI Radar Classification. [Internet] [Thesis]. KTH; 2020. [cited 2020 Sep 27]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273604.

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

Council of Science Editors:

Norén G. Noise Robustness of Convolutional Autoencoders and Neural Networks for LPI Radar Classification. [Thesis]. KTH; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273604

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

28. Johansson, Jimmy. Evaluation of CNN in ESM Data Classification by Perspective of  Military Utility.

Degree: Swedish Defence University, 2020, Swedish Defence University

Modern society has seen an increase in automation using AI in a variety of applications. To keep up with recent development, it is therefore… (more)

Subjects/Keywords: CNN; emitter classification; ESM; spectrogram; military utility; CNN; sändarklassifikation; ES; ESM; spektrogram; militär nytta; Social Sciences Interdisciplinary; Tvärvetenskapliga studier inom samhällsvetenskap

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

APA (6th Edition):

Johansson, J. (2020). Evaluation of CNN in ESM Data Classification by Perspective of  Military Utility. (Thesis). Swedish Defence University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:fhs:diva-9140

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):

Johansson, Jimmy. “Evaluation of CNN in ESM Data Classification by Perspective of  Military Utility.” 2020. Thesis, Swedish Defence University. Accessed September 27, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:fhs:diva-9140.

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

MLA Handbook (7th Edition):

Johansson, Jimmy. “Evaluation of CNN in ESM Data Classification by Perspective of  Military Utility.” 2020. Web. 27 Sep 2020.

Vancouver:

Johansson J. Evaluation of CNN in ESM Data Classification by Perspective of  Military Utility. [Internet] [Thesis]. Swedish Defence University; 2020. [cited 2020 Sep 27]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:fhs:diva-9140.

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

Council of Science Editors:

Johansson J. Evaluation of CNN in ESM Data Classification by Perspective of  Military Utility. [Thesis]. Swedish Defence University; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:fhs:diva-9140

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


University of Manchester

29. Phuycharoen, Mike. Deep Learning Uncovers Genomic Features of Cell-type and State.

Degree: 2019, University of Manchester

 Genomic and epigenomic data are being obtained experimentally at an ever-increasing rate. As datasets become easier and cheaper to collect, computational methods allowing their interpretation… (more)

Subjects/Keywords: Deep learning; CNN; MEIS; HOX; MEF2D; OCT4; ChIP-seq; ATAC-seq

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

APA (6th Edition):

Phuycharoen, M. (2019). Deep Learning Uncovers Genomic Features of Cell-type and State. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:322862

Chicago Manual of Style (16th Edition):

Phuycharoen, Mike. “Deep Learning Uncovers Genomic Features of Cell-type and State.” 2019. Doctoral Dissertation, University of Manchester. Accessed September 27, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:322862.

MLA Handbook (7th Edition):

Phuycharoen, Mike. “Deep Learning Uncovers Genomic Features of Cell-type and State.” 2019. Web. 27 Sep 2020.

Vancouver:

Phuycharoen M. Deep Learning Uncovers Genomic Features of Cell-type and State. [Internet] [Doctoral dissertation]. University of Manchester; 2019. [cited 2020 Sep 27]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:322862.

Council of Science Editors:

Phuycharoen M. Deep Learning Uncovers Genomic Features of Cell-type and State. [Doctoral Dissertation]. University of Manchester; 2019. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:322862


Cornell University

30. Virk, Ishan Singh. Polycystic Kidney Disease MRI Classification and Detection.

Degree: M.S., Information Science, Information Science, 2020, Cornell University

 This proposal outlines the following topics regarding the project of classifying and detecting PKD1 and PKD2 within MRIs: Firstly, it discusses the background of the… (more)

Subjects/Keywords: Classification; Deep Learning; MRI; PKD; Segmentation; Machine Learning; CNN

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

APA (6th Edition):

Virk, I. S. (2020). Polycystic Kidney Disease MRI Classification and Detection. (Masters Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/70226

Chicago Manual of Style (16th Edition):

Virk, Ishan Singh. “Polycystic Kidney Disease MRI Classification and Detection.” 2020. Masters Thesis, Cornell University. Accessed September 27, 2020. http://hdl.handle.net/1813/70226.

MLA Handbook (7th Edition):

Virk, Ishan Singh. “Polycystic Kidney Disease MRI Classification and Detection.” 2020. Web. 27 Sep 2020.

Vancouver:

Virk IS. Polycystic Kidney Disease MRI Classification and Detection. [Internet] [Masters thesis]. Cornell University; 2020. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1813/70226.

Council of Science Editors:

Virk IS. Polycystic Kidney Disease MRI Classification and Detection. [Masters Thesis]. Cornell University; 2020. Available from: http://hdl.handle.net/1813/70226

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