Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for +publisher:"University of North Carolina" +contributor:("Berg, Alexander"). Showing records 1 – 12 of 12 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


University of North Carolina

1. Han, Xufeng. LEARNING WITH MORE DATA AND BETTER MODELS FOR VISUAL SIMILARITY AND DIFFERENTIATION.

Degree: Computer Science, 2016, University of North Carolina

 This thesis studies machine learning problems involved in visual recognition on a variety of computer vision tasks. It attacks the challenge of scaling-up learning to… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Han, X. (2016). LEARNING WITH MORE DATA AND BETTER MODELS FOR VISUAL SIMILARITY AND DIFFERENTIATION. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:e712c6a4-e4ff-4c3b-8646-a6c1c872f042

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):

Han, Xufeng. “LEARNING WITH MORE DATA AND BETTER MODELS FOR VISUAL SIMILARITY AND DIFFERENTIATION.” 2016. Thesis, University of North Carolina. Accessed November 30, 2020. https://cdr.lib.unc.edu/record/uuid:e712c6a4-e4ff-4c3b-8646-a6c1c872f042.

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

MLA Handbook (7th Edition):

Han, Xufeng. “LEARNING WITH MORE DATA AND BETTER MODELS FOR VISUAL SIMILARITY AND DIFFERENTIATION.” 2016. Web. 30 Nov 2020.

Vancouver:

Han X. LEARNING WITH MORE DATA AND BETTER MODELS FOR VISUAL SIMILARITY AND DIFFERENTIATION. [Internet] [Thesis]. University of North Carolina; 2016. [cited 2020 Nov 30]. Available from: https://cdr.lib.unc.edu/record/uuid:e712c6a4-e4ff-4c3b-8646-a6c1c872f042.

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

Council of Science Editors:

Han X. LEARNING WITH MORE DATA AND BETTER MODELS FOR VISUAL SIMILARITY AND DIFFERENTIATION. [Thesis]. University of North Carolina; 2016. Available from: https://cdr.lib.unc.edu/record/uuid:e712c6a4-e4ff-4c3b-8646-a6c1c872f042

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


University of North Carolina

2. Bartel, Jacob. Predictions to Ease Users' Effort in Scalable Sharing.

Degree: Computer Science, 2015, University of North Carolina

 Significant user effort is required to choose recipients of shared information, which grows as the scale of the number of potential or target recipients increases.… (more)

Subjects/Keywords: Computer science; College of Arts and Sciences; Department of Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Bartel, J. (2015). Predictions to Ease Users' Effort in Scalable Sharing. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:279a0cd5-ee7e-4045-8be2-2bf2323107ff

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):

Bartel, Jacob. “Predictions to Ease Users' Effort in Scalable Sharing.” 2015. Thesis, University of North Carolina. Accessed November 30, 2020. https://cdr.lib.unc.edu/record/uuid:279a0cd5-ee7e-4045-8be2-2bf2323107ff.

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

MLA Handbook (7th Edition):

Bartel, Jacob. “Predictions to Ease Users' Effort in Scalable Sharing.” 2015. Web. 30 Nov 2020.

Vancouver:

Bartel J. Predictions to Ease Users' Effort in Scalable Sharing. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2020 Nov 30]. Available from: https://cdr.lib.unc.edu/record/uuid:279a0cd5-ee7e-4045-8be2-2bf2323107ff.

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

Council of Science Editors:

Bartel J. Predictions to Ease Users' Effort in Scalable Sharing. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:279a0cd5-ee7e-4045-8be2-2bf2323107ff

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


University of North Carolina

3. Ordonez Roman, Vicente. Language and Perceptual Categorization in Computational Visual Recognition.

Degree: Computer Science, 2015, University of North Carolina

 Computational visual recognition or giving computers the ability to understand images as well as humans do is a core problem in Computer Vision. Traditional recognition… (more)

Subjects/Keywords: Computer science; College of Arts and Sciences; Department of Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Ordonez Roman, V. (2015). Language and Perceptual Categorization in Computational Visual Recognition. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:188ef51f-d3dc-4216-97ea-07da5109a1a6

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):

Ordonez Roman, Vicente. “Language and Perceptual Categorization in Computational Visual Recognition.” 2015. Thesis, University of North Carolina. Accessed November 30, 2020. https://cdr.lib.unc.edu/record/uuid:188ef51f-d3dc-4216-97ea-07da5109a1a6.

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

MLA Handbook (7th Edition):

Ordonez Roman, Vicente. “Language and Perceptual Categorization in Computational Visual Recognition.” 2015. Web. 30 Nov 2020.

Vancouver:

Ordonez Roman V. Language and Perceptual Categorization in Computational Visual Recognition. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2020 Nov 30]. Available from: https://cdr.lib.unc.edu/record/uuid:188ef51f-d3dc-4216-97ea-07da5109a1a6.

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

Council of Science Editors:

Ordonez Roman V. Language and Perceptual Categorization in Computational Visual Recognition. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:188ef51f-d3dc-4216-97ea-07da5109a1a6

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


University of North Carolina

4. Heinly, Jared. Toward Efficient and Robust Large-Scale Structure-from-Motion Systems.

Degree: Computer Science, 2015, University of North Carolina

 The ever-increasing number of images that are uploaded and shared on the Internet has recently been leveraged by computer vision researchers to extract 3D information… (more)

Subjects/Keywords: Computer science; College of Arts and Sciences; Department of Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Heinly, J. (2015). Toward Efficient and Robust Large-Scale Structure-from-Motion Systems. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:49e7a86a-d94e-4d47-b5ae-0d6a015e4725

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):

Heinly, Jared. “Toward Efficient and Robust Large-Scale Structure-from-Motion Systems.” 2015. Thesis, University of North Carolina. Accessed November 30, 2020. https://cdr.lib.unc.edu/record/uuid:49e7a86a-d94e-4d47-b5ae-0d6a015e4725.

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

MLA Handbook (7th Edition):

Heinly, Jared. “Toward Efficient and Robust Large-Scale Structure-from-Motion Systems.” 2015. Web. 30 Nov 2020.

Vancouver:

Heinly J. Toward Efficient and Robust Large-Scale Structure-from-Motion Systems. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2020 Nov 30]. Available from: https://cdr.lib.unc.edu/record/uuid:49e7a86a-d94e-4d47-b5ae-0d6a015e4725.

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

Council of Science Editors:

Heinly J. Toward Efficient and Robust Large-Scale Structure-from-Motion Systems. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:49e7a86a-d94e-4d47-b5ae-0d6a015e4725

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


University of North Carolina

5. Kiapour, Mohammadhadi. LARGE SCALE VISUAL RECOGNITION OF CLOTHING, PEOPLE AND STYLES.

Degree: Computer Science, 2015, University of North Carolina

 Clothing recognition is a societally and commercially important yet extremely challenging problem due to large variations in clothing appearance, layering, style, body shape and pose.… (more)

Subjects/Keywords: Computer science; College of Arts and Sciences; Department of Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Kiapour, M. (2015). LARGE SCALE VISUAL RECOGNITION OF CLOTHING, PEOPLE AND STYLES. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:d5241918-b3f4-4089-86de-f9d957179775

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):

Kiapour, Mohammadhadi. “LARGE SCALE VISUAL RECOGNITION OF CLOTHING, PEOPLE AND STYLES.” 2015. Thesis, University of North Carolina. Accessed November 30, 2020. https://cdr.lib.unc.edu/record/uuid:d5241918-b3f4-4089-86de-f9d957179775.

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

MLA Handbook (7th Edition):

Kiapour, Mohammadhadi. “LARGE SCALE VISUAL RECOGNITION OF CLOTHING, PEOPLE AND STYLES.” 2015. Web. 30 Nov 2020.

Vancouver:

Kiapour M. LARGE SCALE VISUAL RECOGNITION OF CLOTHING, PEOPLE AND STYLES. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2020 Nov 30]. Available from: https://cdr.lib.unc.edu/record/uuid:d5241918-b3f4-4089-86de-f9d957179775.

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

Council of Science Editors:

Kiapour M. LARGE SCALE VISUAL RECOGNITION OF CLOTHING, PEOPLE AND STYLES. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:d5241918-b3f4-4089-86de-f9d957179775

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


University of North Carolina

6. Taylor, Teryl. Using Context to Improve Network-based Exploit Kit Detection.

Degree: Computer Science, 2016, University of North Carolina

 Today, our computers are routinely compromised while performing seemingly innocuous activities like reading articles on trusted websites (e.g., the NY Times). These compromises are perpetrated… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Taylor, T. (2016). Using Context to Improve Network-based Exploit Kit Detection. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:71d5279c-99b1-4f99-b8d2-d7a2b82dae8a

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):

Taylor, Teryl. “Using Context to Improve Network-based Exploit Kit Detection.” 2016. Thesis, University of North Carolina. Accessed November 30, 2020. https://cdr.lib.unc.edu/record/uuid:71d5279c-99b1-4f99-b8d2-d7a2b82dae8a.

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

MLA Handbook (7th Edition):

Taylor, Teryl. “Using Context to Improve Network-based Exploit Kit Detection.” 2016. Web. 30 Nov 2020.

Vancouver:

Taylor T. Using Context to Improve Network-based Exploit Kit Detection. [Internet] [Thesis]. University of North Carolina; 2016. [cited 2020 Nov 30]. Available from: https://cdr.lib.unc.edu/record/uuid:71d5279c-99b1-4f99-b8d2-d7a2b82dae8a.

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

Council of Science Editors:

Taylor T. Using Context to Improve Network-based Exploit Kit Detection. [Thesis]. University of North Carolina; 2016. Available from: https://cdr.lib.unc.edu/record/uuid:71d5279c-99b1-4f99-b8d2-d7a2b82dae8a

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


University of North Carolina

7. Cao, Tian. Coupled Dictionary Learning for Image Analysis.

Degree: Computer Science, 2016, University of North Carolina

 Modern imaging technologies provide different ways to visualize various objects ranging from molecules in a cell to the tissue of a human body. Images from… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Cao, T. (2016). Coupled Dictionary Learning for Image Analysis. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:3947027b-8683-4c77-aa06-16d03417bc25

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

Chicago Manual of Style (16th Edition):

Cao, Tian. “Coupled Dictionary Learning for Image Analysis.” 2016. Thesis, University of North Carolina. Accessed November 30, 2020. https://cdr.lib.unc.edu/record/uuid:3947027b-8683-4c77-aa06-16d03417bc25.

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

MLA Handbook (7th Edition):

Cao, Tian. “Coupled Dictionary Learning for Image Analysis.” 2016. Web. 30 Nov 2020.

Vancouver:

Cao T. Coupled Dictionary Learning for Image Analysis. [Internet] [Thesis]. University of North Carolina; 2016. [cited 2020 Nov 30]. Available from: https://cdr.lib.unc.edu/record/uuid:3947027b-8683-4c77-aa06-16d03417bc25.

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

Council of Science Editors:

Cao T. Coupled Dictionary Learning for Image Analysis. [Thesis]. University of North Carolina; 2016. Available from: https://cdr.lib.unc.edu/record/uuid:3947027b-8683-4c77-aa06-16d03417bc25

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


University of North Carolina

8. Liu, Wei. Localizing Objects Fast and Accurately.

Degree: Computer Science, 2016, University of North Carolina

 A fundamental problem in computer vision is knowing what is in the image and where it is. We develop models to localize objects of multiple… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Liu, W. (2016). Localizing Objects Fast and Accurately. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:46218f57-e071-4cf8-9f51-0065bede73f9

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

Chicago Manual of Style (16th Edition):

Liu, Wei. “Localizing Objects Fast and Accurately.” 2016. Thesis, University of North Carolina. Accessed November 30, 2020. https://cdr.lib.unc.edu/record/uuid:46218f57-e071-4cf8-9f51-0065bede73f9.

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

MLA Handbook (7th Edition):

Liu, Wei. “Localizing Objects Fast and Accurately.” 2016. Web. 30 Nov 2020.

Vancouver:

Liu W. Localizing Objects Fast and Accurately. [Internet] [Thesis]. University of North Carolina; 2016. [cited 2020 Nov 30]. Available from: https://cdr.lib.unc.edu/record/uuid:46218f57-e071-4cf8-9f51-0065bede73f9.

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

Council of Science Editors:

Liu W. Localizing Objects Fast and Accurately. [Thesis]. University of North Carolina; 2016. Available from: https://cdr.lib.unc.edu/record/uuid:46218f57-e071-4cf8-9f51-0065bede73f9

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


University of North Carolina

9. Kim, Hyo Jin. Learning Adaptive Representations for Image Retrieval and Recognition.

Degree: Computer Science, 2018, University of North Carolina

 Content-based image retrieval is a core problem in computer vision. It has a wide range of application such as object and place recognition, digital library… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Kim, H. J. (2018). Learning Adaptive Representations for Image Retrieval and Recognition. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:fe578de7-bc9f-461b-815a-83dcfd923878

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, Hyo Jin. “Learning Adaptive Representations for Image Retrieval and Recognition.” 2018. Thesis, University of North Carolina. Accessed November 30, 2020. https://cdr.lib.unc.edu/record/uuid:fe578de7-bc9f-461b-815a-83dcfd923878.

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

MLA Handbook (7th Edition):

Kim, Hyo Jin. “Learning Adaptive Representations for Image Retrieval and Recognition.” 2018. Web. 30 Nov 2020.

Vancouver:

Kim HJ. Learning Adaptive Representations for Image Retrieval and Recognition. [Internet] [Thesis]. University of North Carolina; 2018. [cited 2020 Nov 30]. Available from: https://cdr.lib.unc.edu/record/uuid:fe578de7-bc9f-461b-815a-83dcfd923878.

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

Council of Science Editors:

Kim HJ. Learning Adaptive Representations for Image Retrieval and Recognition. [Thesis]. University of North Carolina; 2018. Available from: https://cdr.lib.unc.edu/record/uuid:fe578de7-bc9f-461b-815a-83dcfd923878

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


University of North Carolina

10. Hong, Yi. Image and Shape Analysis for Spatiotemporal Data.

Degree: Computer Science, 2016, University of North Carolina

 In analyzing brain development or identifying disease it is important to understand anatomical age-related changes and shape differences. Data for these studies is frequently spatiotemporal… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Hong, Y. (2016). Image and Shape Analysis for Spatiotemporal Data. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:b885e43a-a3db-4ed3-8758-a3223044fe52

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):

Hong, Yi. “Image and Shape Analysis for Spatiotemporal Data.” 2016. Thesis, University of North Carolina. Accessed November 30, 2020. https://cdr.lib.unc.edu/record/uuid:b885e43a-a3db-4ed3-8758-a3223044fe52.

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

MLA Handbook (7th Edition):

Hong, Yi. “Image and Shape Analysis for Spatiotemporal Data.” 2016. Web. 30 Nov 2020.

Vancouver:

Hong Y. Image and Shape Analysis for Spatiotemporal Data. [Internet] [Thesis]. University of North Carolina; 2016. [cited 2020 Nov 30]. Available from: https://cdr.lib.unc.edu/record/uuid:b885e43a-a3db-4ed3-8758-a3223044fe52.

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

Council of Science Editors:

Hong Y. Image and Shape Analysis for Spatiotemporal Data. [Thesis]. University of North Carolina; 2016. Available from: https://cdr.lib.unc.edu/record/uuid:b885e43a-a3db-4ed3-8758-a3223044fe52

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


University of North Carolina

11. Vittayakorn, Sirion. Visual attribute discovery and analyses from Web data.

Degree: Computer Science, 2016, University of North Carolina

 Visual attributes are important for describing and understanding an object’s appearance. For an object classification or recognition task, an algorithm needs to infer the visual… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Vittayakorn, S. (2016). Visual attribute discovery and analyses from Web data. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:e99f13f0-8689-49cc-a15d-3269cb0e4732

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):

Vittayakorn, Sirion. “Visual attribute discovery and analyses from Web data.” 2016. Thesis, University of North Carolina. Accessed November 30, 2020. https://cdr.lib.unc.edu/record/uuid:e99f13f0-8689-49cc-a15d-3269cb0e4732.

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

MLA Handbook (7th Edition):

Vittayakorn, Sirion. “Visual attribute discovery and analyses from Web data.” 2016. Web. 30 Nov 2020.

Vancouver:

Vittayakorn S. Visual attribute discovery and analyses from Web data. [Internet] [Thesis]. University of North Carolina; 2016. [cited 2020 Nov 30]. Available from: https://cdr.lib.unc.edu/record/uuid:e99f13f0-8689-49cc-a15d-3269cb0e4732.

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

Council of Science Editors:

Vittayakorn S. Visual attribute discovery and analyses from Web data. [Thesis]. University of North Carolina; 2016. Available from: https://cdr.lib.unc.edu/record/uuid:e99f13f0-8689-49cc-a15d-3269cb0e4732

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


University of North Carolina

12. Wang, Ke. Towards Efficient 3D Reconstructions from High-Resolution Satellite Imagery.

Degree: Computer Science, 2018, University of North Carolina

 Recent years have witnessed the rapid growth of commercial satellite imagery. Compared with other imaging products, such as aerial or streetview imagery, modern satellite images… (more)

Subjects/Keywords: College of Arts and Sciences; Department of Computer Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Wang, K. (2018). Towards Efficient 3D Reconstructions from High-Resolution Satellite Imagery. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:a342d2a8-51a5-44c4-b4b5-8d9a1ac68700

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, Ke. “Towards Efficient 3D Reconstructions from High-Resolution Satellite Imagery.” 2018. Thesis, University of North Carolina. Accessed November 30, 2020. https://cdr.lib.unc.edu/record/uuid:a342d2a8-51a5-44c4-b4b5-8d9a1ac68700.

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

MLA Handbook (7th Edition):

Wang, Ke. “Towards Efficient 3D Reconstructions from High-Resolution Satellite Imagery.” 2018. Web. 30 Nov 2020.

Vancouver:

Wang K. Towards Efficient 3D Reconstructions from High-Resolution Satellite Imagery. [Internet] [Thesis]. University of North Carolina; 2018. [cited 2020 Nov 30]. Available from: https://cdr.lib.unc.edu/record/uuid:a342d2a8-51a5-44c4-b4b5-8d9a1ac68700.

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

Council of Science Editors:

Wang K. Towards Efficient 3D Reconstructions from High-Resolution Satellite Imagery. [Thesis]. University of North Carolina; 2018. Available from: https://cdr.lib.unc.edu/record/uuid:a342d2a8-51a5-44c4-b4b5-8d9a1ac68700

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

.