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You searched for +publisher:"University of Texas – Austin" +contributor:("Grauman, Kristen Lorraine, 1979-"). Showing records 1 – 15 of 15 total matches.

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1. Xia, Lu, active 21st century. Human detection and action recognition using depth information by Kinect.

Degree: Electrical and Computer Engineering, 2012, University of Texas – Austin

 Traditional computer vision algorithms depend on information taken by visible-light cameras. But there are inherent limitations of this data source, e.g. they are sensitive to… (more)

Subjects/Keywords: Human detection; Action recognition; Kinect; Depth image; 3D; View-invariant

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

APA (6th Edition):

Xia, Lu, a. 2. c. (2012). Human detection and action recognition using depth information by Kinect. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5509

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):

Xia, Lu, active 21st century. “Human detection and action recognition using depth information by Kinect.” 2012. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/ETD-UT-2012-05-5509.

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

MLA Handbook (7th Edition):

Xia, Lu, active 21st century. “Human detection and action recognition using depth information by Kinect.” 2012. Web. 23 Apr 2019.

Vancouver:

Xia, Lu a2c. Human detection and action recognition using depth information by Kinect. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5509.

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

Council of Science Editors:

Xia, Lu a2c. Human detection and action recognition using depth information by Kinect. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5509

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

2. Hwang, Sung Ju. Discriminative object categorization with external semantic knowledge.

Degree: Computer Sciences, 2013, University of Texas – Austin

 Visual object category recognition is one of the most challenging problems in computer vision. Even assuming that we can obtain a near-perfect instance level representation… (more)

Subjects/Keywords: Computer vision; Machine learning; Object categorization; Object recognition; Feature learning; Metric learning; Multitask learning; Multiple kernel learning; Embedding; Manifold learning; Regularization method; Structured sparsity; Structured regularization; Hierarchical model

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

APA (6th Edition):

Hwang, S. J. (2013). Discriminative object categorization with external semantic knowledge. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/21320

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):

Hwang, Sung Ju. “Discriminative object categorization with external semantic knowledge.” 2013. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/21320.

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

MLA Handbook (7th Edition):

Hwang, Sung Ju. “Discriminative object categorization with external semantic knowledge.” 2013. Web. 23 Apr 2019.

Vancouver:

Hwang SJ. Discriminative object categorization with external semantic knowledge. [Internet] [Thesis]. University of Texas – Austin; 2013. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/21320.

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

Council of Science Editors:

Hwang SJ. Discriminative object categorization with external semantic knowledge. [Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/21320

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

3. Kim, Jaechul. Region detection and matching for object recognition.

Degree: Computer Sciences, 2013, University of Texas – Austin

 In this thesis, I explore region detection and consider its impact on image matching for exemplar-based object recognition. Detecting regions is important to provide semantically… (more)

Subjects/Keywords: Computer vision; Object recognition; Feature detection; Segmentation; Image matching; Shape

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APA (6th Edition):

Kim, J. (2013). Region detection and matching for object recognition. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/21261

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):

Kim, Jaechul. “Region detection and matching for object recognition.” 2013. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/21261.

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

MLA Handbook (7th Edition):

Kim, Jaechul. “Region detection and matching for object recognition.” 2013. Web. 23 Apr 2019.

Vancouver:

Kim J. Region detection and matching for object recognition. [Internet] [Thesis]. University of Texas – Austin; 2013. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/21261.

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

Council of Science Editors:

Kim J. Region detection and matching for object recognition. [Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/21261

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

4. Bandla, Sunil. Active learning of an action detector on untrimmed videos.

Degree: Computer Sciences, 2013, University of Texas – Austin

 Collecting and annotating videos of realistic human actions is tedious, yet critical for training action recognition systems. We propose a method to actively request the… (more)

Subjects/Keywords: Computer vision; Action detection; Active learning

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

APA (6th Edition):

Bandla, S. (2013). Active learning of an action detector on untrimmed videos. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/25260

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):

Bandla, Sunil. “Active learning of an action detector on untrimmed videos.” 2013. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/25260.

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

MLA Handbook (7th Edition):

Bandla, Sunil. “Active learning of an action detector on untrimmed videos.” 2013. Web. 23 Apr 2019.

Vancouver:

Bandla S. Active learning of an action detector on untrimmed videos. [Internet] [Thesis]. University of Texas – Austin; 2013. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/25260.

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

Council of Science Editors:

Bandla S. Active learning of an action detector on untrimmed videos. [Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/25260

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

5. Kovashka, Adriana Ivanova. Interactive image search with attributes.

Degree: Computer Sciences, 2014, University of Texas – Austin

 An image retrieval system needs to be able to communicate with people using a common language, if it is to serve its user's information need.… (more)

Subjects/Keywords: Computer vision; Attributes; Image retrieval; Relevance feedback; Object recognition; Active learning; Personalization; Vision and language

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

APA (6th Edition):

Kovashka, A. I. (2014). Interactive image search with attributes. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/25986

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):

Kovashka, Adriana Ivanova. “Interactive image search with attributes.” 2014. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/25986.

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

MLA Handbook (7th Edition):

Kovashka, Adriana Ivanova. “Interactive image search with attributes.” 2014. Web. 23 Apr 2019.

Vancouver:

Kovashka AI. Interactive image search with attributes. [Internet] [Thesis]. University of Texas – Austin; 2014. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/25986.

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

Council of Science Editors:

Kovashka AI. Interactive image search with attributes. [Thesis]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/25986

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


University of Texas – Austin

6. Kelle, Joshua Allen. Frugal Forests : learning a dynamic and cost sensitive feature extraction policy for anytime activity classification.

Degree: Computer Sciences, 2018, University of Texas – Austin

 Many approaches to activity classification use supervised learning and so rely on extracting some form of features from the video. This feature extraction process can… (more)

Subjects/Keywords: Frugal Forest; Feature extraction; Activity recognition; Cost; Dynamic

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APA (6th Edition):

Kelle, J. A. (2018). Frugal Forests : learning a dynamic and cost sensitive feature extraction policy for anytime activity classification. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68857

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):

Kelle, Joshua Allen. “Frugal Forests : learning a dynamic and cost sensitive feature extraction policy for anytime activity classification.” 2018. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/68857.

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

MLA Handbook (7th Edition):

Kelle, Joshua Allen. “Frugal Forests : learning a dynamic and cost sensitive feature extraction policy for anytime activity classification.” 2018. Web. 23 Apr 2019.

Vancouver:

Kelle JA. Frugal Forests : learning a dynamic and cost sensitive feature extraction policy for anytime activity classification. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/68857.

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

Council of Science Editors:

Kelle JA. Frugal Forests : learning a dynamic and cost sensitive feature extraction policy for anytime activity classification. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68857

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


University of Texas – Austin

7. Hwang, Sung Ju. Reading between the lines : object localization using implicit cues from image tags.

Degree: Computer Sciences, 2010, University of Texas – Austin

 Current uses of tagged images typically exploit only the most explicit information: the link between the nouns named and the objects present somewhere in the… (more)

Subjects/Keywords: Computer vision; Object recognition; Object detection

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

APA (6th Edition):

Hwang, S. J. (2010). Reading between the lines : object localization using implicit cues from image tags. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-05-1514

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):

Hwang, Sung Ju. “Reading between the lines : object localization using implicit cues from image tags.” 2010. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/ETD-UT-2010-05-1514.

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

MLA Handbook (7th Edition):

Hwang, Sung Ju. “Reading between the lines : object localization using implicit cues from image tags.” 2010. Web. 23 Apr 2019.

Vancouver:

Hwang SJ. Reading between the lines : object localization using implicit cues from image tags. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-05-1514.

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

Council of Science Editors:

Hwang SJ. Reading between the lines : object localization using implicit cues from image tags. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-05-1514

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


University of Texas – Austin

8. Sheshadri, Aashish. A collaborative approach to IR evaluation.

Degree: Computer Sciences, 2014, University of Texas – Austin

 In this thesis we investigate two main problems: 1) inferring consensus from disparate inputs to improve quality of crowd contributed data; and 2) developing a… (more)

Subjects/Keywords: Crowdsourcing; Evaluation; Information retrieval; Simulation

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

APA (6th Edition):

Sheshadri, A. (2014). A collaborative approach to IR evaluation. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/25910

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):

Sheshadri, Aashish. “A collaborative approach to IR evaluation.” 2014. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/25910.

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

MLA Handbook (7th Edition):

Sheshadri, Aashish. “A collaborative approach to IR evaluation.” 2014. Web. 23 Apr 2019.

Vancouver:

Sheshadri A. A collaborative approach to IR evaluation. [Internet] [Thesis]. University of Texas – Austin; 2014. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/25910.

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

Council of Science Editors:

Sheshadri A. A collaborative approach to IR evaluation. [Thesis]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/25910

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


University of Texas – Austin

9. Chen, Chao-Yeh. Clues from the beaten path : location estimation with bursty sequences of tourist photos: Location estimation with bursty sequences of tourist photos.

Degree: Electrical and Computer Engineering, 2010, University of Texas – Austin

 Existing methods for image-based location estimation generally attempt to recognize every photo independently, and their resulting reliance on strong visual feature matches makes them most… (more)

Subjects/Keywords: Location estimation; Hidden Markov Model; Object recognition

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

APA (6th Edition):

Chen, C. (2010). Clues from the beaten path : location estimation with bursty sequences of tourist photos: Location estimation with bursty sequences of tourist photos. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-12-2301

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, Chao-Yeh. “Clues from the beaten path : location estimation with bursty sequences of tourist photos: Location estimation with bursty sequences of tourist photos.” 2010. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/ETD-UT-2010-12-2301.

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

MLA Handbook (7th Edition):

Chen, Chao-Yeh. “Clues from the beaten path : location estimation with bursty sequences of tourist photos: Location estimation with bursty sequences of tourist photos.” 2010. Web. 23 Apr 2019.

Vancouver:

Chen C. Clues from the beaten path : location estimation with bursty sequences of tourist photos: Location estimation with bursty sequences of tourist photos. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-12-2301.

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

Council of Science Editors:

Chen C. Clues from the beaten path : location estimation with bursty sequences of tourist photos: Location estimation with bursty sequences of tourist photos. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-12-2301

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


University of Texas – Austin

10. Chen, Chao-Yeh. Learning human activities and poses with interconnected data sources.

Degree: Computer Sciences, 2016, University of Texas – Austin

 Understanding human actions and poses in images or videos is a challenging problem in computer vision. There are different topics related to this problem such… (more)

Subjects/Keywords: Activity recognition; Activity detection

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

APA (6th Edition):

Chen, C. (2016). Learning human activities and poses with interconnected data sources. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/40260

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, Chao-Yeh. “Learning human activities and poses with interconnected data sources.” 2016. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/40260.

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

MLA Handbook (7th Edition):

Chen, Chao-Yeh. “Learning human activities and poses with interconnected data sources.” 2016. Web. 23 Apr 2019.

Vancouver:

Chen C. Learning human activities and poses with interconnected data sources. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/40260.

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

Council of Science Editors:

Chen C. Learning human activities and poses with interconnected data sources. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/40260

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


University of Texas – Austin

11. Jain, Suyog Dutt. Human machine collaboration for foreground segmentation in images and videos.

Degree: Computer Sciences, 2018, University of Texas – Austin

 Foreground segmentation is defined as the problem of generating pixel level foreground masks for all the objects in a given image or video. Accurate foreground… (more)

Subjects/Keywords: Computer vision; Crowdsourcing; Human machine collaboration; Image and video segmentation; Image segmentation; Video segmentation; Foreground segmentation; Object segmentation

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

APA (6th Edition):

Jain, S. D. (2018). Human machine collaboration for foreground segmentation in images and videos. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63453

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):

Jain, Suyog Dutt. “Human machine collaboration for foreground segmentation in images and videos.” 2018. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/63453.

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

MLA Handbook (7th Edition):

Jain, Suyog Dutt. “Human machine collaboration for foreground segmentation in images and videos.” 2018. Web. 23 Apr 2019.

Vancouver:

Jain SD. Human machine collaboration for foreground segmentation in images and videos. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/63453.

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

Council of Science Editors:

Jain SD. Human machine collaboration for foreground segmentation in images and videos. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/63453

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


University of Texas – Austin

12. -6888-3095. Embodied learning for visual recognition.

Degree: Electrical and Computer Engineering, 2017, University of Texas – Austin

 The field of visual recognition in recent years has come to rely on large expensively curated and manually labeled "bags of disembodied images". In the… (more)

Subjects/Keywords: Computer vision; Unsupervised learning; Embodied learning

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

APA (6th Edition):

-6888-3095. (2017). Embodied learning for visual recognition. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63489

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

Chicago Manual of Style (16th Edition):

-6888-3095. “Embodied learning for visual recognition.” 2017. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/63489.

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

MLA Handbook (7th Edition):

-6888-3095. “Embodied learning for visual recognition.” 2017. Web. 23 Apr 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-6888-3095. Embodied learning for visual recognition. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/63489.

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

Council of Science Editors:

-6888-3095. Embodied learning for visual recognition. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/63489

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

13. Xu, Changhai, 1977-. Steps towards the object semantic hierarchy.

Degree: Computer Sciences, 2011, University of Texas – Austin

 An intelligent robot must be able to perceive and reason robustly about its world in terms of objects, among other foundational concepts. The robot can… (more)

Subjects/Keywords: Object semantic hierarchy; 3D object model; Object tracking; Object segmentation; Motion segmentation; 3D pose estimation

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

APA (6th Edition):

Xu, Changhai, 1. (2011). Steps towards the object semantic hierarchy. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-08-3797

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, Changhai, 1977-. “Steps towards the object semantic hierarchy.” 2011. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/ETD-UT-2011-08-3797.

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

MLA Handbook (7th Edition):

Xu, Changhai, 1977-. “Steps towards the object semantic hierarchy.” 2011. Web. 23 Apr 2019.

Vancouver:

Xu, Changhai 1. Steps towards the object semantic hierarchy. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-08-3797.

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

Council of Science Editors:

Xu, Changhai 1. Steps towards the object semantic hierarchy. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-08-3797

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


University of Texas – Austin

14. Vijayanarasimhan, Sudheendra. Active visual category learning.

Degree: Computer Sciences, 2011, University of Texas – Austin

 Visual recognition research develops algorithms and representations to autonomously recognize visual entities such as objects, actions, and attributes. The traditional protocol involves manually collecting training… (more)

Subjects/Keywords: Artificial intelligence; Active learning; Object recognition; Object detection; Cost-sensitive learning; Multi-level learning; Budgeted learning; Large-scale active learning; Live learning; Machine learning; Visual recognition system

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

APA (6th Edition):

Vijayanarasimhan, S. (2011). Active visual category learning. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-05-3014

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):

Vijayanarasimhan, Sudheendra. “Active visual category learning.” 2011. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/ETD-UT-2011-05-3014.

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

MLA Handbook (7th Edition):

Vijayanarasimhan, Sudheendra. “Active visual category learning.” 2011. Web. 23 Apr 2019.

Vancouver:

Vijayanarasimhan S. Active visual category learning. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3014.

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

Council of Science Editors:

Vijayanarasimhan S. Active visual category learning. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3014

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


University of Texas – Austin

15. Lee, Yong Jae, 1984-. Visual object category discovery in images and videos.

Degree: Electrical and Computer Engineering, 2012, University of Texas – Austin

 The current trend in visual recognition research is to place a strict division between the supervised and unsupervised learning paradigms, which is problematic for two… (more)

Subjects/Keywords: Unsupervised learning; Visual category discovery; Image and video segmentation; Video summarization

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

APA (6th Edition):

Lee, Yong Jae, 1. (2012). Visual object category discovery in images and videos. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5381

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, Yong Jae, 1984-. “Visual object category discovery in images and videos.” 2012. Thesis, University of Texas – Austin. Accessed April 23, 2019. http://hdl.handle.net/2152/ETD-UT-2012-05-5381.

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

MLA Handbook (7th Edition):

Lee, Yong Jae, 1984-. “Visual object category discovery in images and videos.” 2012. Web. 23 Apr 2019.

Vancouver:

Lee, Yong Jae 1. Visual object category discovery in images and videos. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Apr 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5381.

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

Council of Science Editors:

Lee, Yong Jae 1. Visual object category discovery in images and videos. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5381

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

.