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You searched for +publisher:"University of North Carolina" +contributor:("Jojic, Vladimir"). Showing records 1 – 11 of 11 total matches.

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University of North Carolina

1. Huang, Shunping. Correcting Reference Bias in High-throughput Sequencing Analysis.

Degree: Computer Science, 2015, University of North Carolina

 Mapping reads to a reference sequence is a common step when analyzing high throughput sequencing data. The choice of reference is critical because its effect… (more)

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

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

APA (6th Edition):

Huang, S. (2015). Correcting Reference Bias in High-throughput Sequencing Analysis. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:44569641-9dd5-4305-845a-4b0b847f0b4a

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):

Huang, Shunping. “Correcting Reference Bias in High-throughput Sequencing Analysis.” 2015. Thesis, University of North Carolina. Accessed November 29, 2020. https://cdr.lib.unc.edu/record/uuid:44569641-9dd5-4305-845a-4b0b847f0b4a.

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

MLA Handbook (7th Edition):

Huang, Shunping. “Correcting Reference Bias in High-throughput Sequencing Analysis.” 2015. Web. 29 Nov 2020.

Vancouver:

Huang S. Correcting Reference Bias in High-throughput Sequencing Analysis. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2020 Nov 29]. Available from: https://cdr.lib.unc.edu/record/uuid:44569641-9dd5-4305-845a-4b0b847f0b4a.

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

Council of Science Editors:

Huang S. Correcting Reference Bias in High-throughput Sequencing Analysis. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:44569641-9dd5-4305-845a-4b0b847f0b4a

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

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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 29, 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. 29 Nov 2020.

Vancouver:

Bartel J. Predictions to Ease Users' Effort in Scalable Sharing. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2020 Nov 29]. 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. 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

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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 29, 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. 29 Nov 2020.

Vancouver:

Cao T. Coupled Dictionary Learning for Image Analysis. [Internet] [Thesis]. University of North Carolina; 2016. [cited 2020 Nov 29]. 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

4. Yang, Xiao. Uncertainty Quantification, Image Synthesis and Deformation Prediction for Image Registration.

Degree: Computer Science, 2017, University of North Carolina

 Image registration is essential for medical image analysis to provide spatial correspondences. It is a difficult problem due to the modeling complexity of image appearance… (more)

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

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APA (6th Edition):

Yang, X. (2017). Uncertainty Quantification, Image Synthesis and Deformation Prediction for Image Registration. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:a381c258-38eb-4a3f-950b-a19bf7ed3bf7

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):

Yang, Xiao. “Uncertainty Quantification, Image Synthesis and Deformation Prediction for Image Registration.” 2017. Thesis, University of North Carolina. Accessed November 29, 2020. https://cdr.lib.unc.edu/record/uuid:a381c258-38eb-4a3f-950b-a19bf7ed3bf7.

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

MLA Handbook (7th Edition):

Yang, Xiao. “Uncertainty Quantification, Image Synthesis and Deformation Prediction for Image Registration.” 2017. Web. 29 Nov 2020.

Vancouver:

Yang X. Uncertainty Quantification, Image Synthesis and Deformation Prediction for Image Registration. [Internet] [Thesis]. University of North Carolina; 2017. [cited 2020 Nov 29]. Available from: https://cdr.lib.unc.edu/record/uuid:a381c258-38eb-4a3f-950b-a19bf7ed3bf7.

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

Council of Science Editors:

Yang X. Uncertainty Quantification, Image Synthesis and Deformation Prediction for Image Registration. [Thesis]. University of North Carolina; 2017. Available from: https://cdr.lib.unc.edu/record/uuid:a381c258-38eb-4a3f-950b-a19bf7ed3bf7

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


University of North Carolina

5. Bowen, Chris. Robots that Learn and Plan — Unifying Robot Learning and Motion Planning for Generalized Task Execution.

Degree: Computer Science, 2018, University of North Carolina

 Robots have the potential to assist people with a variety of everyday tasks, but to achieve that potential robots require software capable of planning and… (more)

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

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APA (6th Edition):

Bowen, C. (2018). Robots that Learn and Plan — Unifying Robot Learning and Motion Planning for Generalized Task Execution. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:3e8f2b19-5574-4411-a0a3-89bf7918ffde

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):

Bowen, Chris. “Robots that Learn and Plan — Unifying Robot Learning and Motion Planning for Generalized Task Execution.” 2018. Thesis, University of North Carolina. Accessed November 29, 2020. https://cdr.lib.unc.edu/record/uuid:3e8f2b19-5574-4411-a0a3-89bf7918ffde.

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

MLA Handbook (7th Edition):

Bowen, Chris. “Robots that Learn and Plan — Unifying Robot Learning and Motion Planning for Generalized Task Execution.” 2018. Web. 29 Nov 2020.

Vancouver:

Bowen C. Robots that Learn and Plan — Unifying Robot Learning and Motion Planning for Generalized Task Execution. [Internet] [Thesis]. University of North Carolina; 2018. [cited 2020 Nov 29]. Available from: https://cdr.lib.unc.edu/record/uuid:3e8f2b19-5574-4411-a0a3-89bf7918ffde.

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

Council of Science Editors:

Bowen C. Robots that Learn and Plan — Unifying Robot Learning and Motion Planning for Generalized Task Execution. [Thesis]. University of North Carolina; 2018. Available from: https://cdr.lib.unc.edu/record/uuid:3e8f2b19-5574-4411-a0a3-89bf7918ffde

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


University of North Carolina

6. Zheng, Enliang. TOWARD 3D RECONSTRUCTION OF STATIC AND DYNAMIC OBJECTS.

Degree: Computer Science, 2016, University of North Carolina

 The goal of image-based 3D reconstruction is to construct a spatial understanding of the world from a collection of images. For applications that seek to… (more)

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

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APA (6th Edition):

Zheng, E. (2016). TOWARD 3D RECONSTRUCTION OF STATIC AND DYNAMIC OBJECTS. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:adaabbef-0021-4d4b-87b3-4b6f9985d97d

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):

Zheng, Enliang. “TOWARD 3D RECONSTRUCTION OF STATIC AND DYNAMIC OBJECTS.” 2016. Thesis, University of North Carolina. Accessed November 29, 2020. https://cdr.lib.unc.edu/record/uuid:adaabbef-0021-4d4b-87b3-4b6f9985d97d.

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

MLA Handbook (7th Edition):

Zheng, Enliang. “TOWARD 3D RECONSTRUCTION OF STATIC AND DYNAMIC OBJECTS.” 2016. Web. 29 Nov 2020.

Vancouver:

Zheng E. TOWARD 3D RECONSTRUCTION OF STATIC AND DYNAMIC OBJECTS. [Internet] [Thesis]. University of North Carolina; 2016. [cited 2020 Nov 29]. Available from: https://cdr.lib.unc.edu/record/uuid:adaabbef-0021-4d4b-87b3-4b6f9985d97d.

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

Council of Science Editors:

Zheng E. TOWARD 3D RECONSTRUCTION OF STATIC AND DYNAMIC OBJECTS. [Thesis]. University of North Carolina; 2016. Available from: https://cdr.lib.unc.edu/record/uuid:adaabbef-0021-4d4b-87b3-4b6f9985d97d

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


University of North Carolina

7. Fu, Chen-Ping. Analysis of Admixed Animals using Indirect Haplotype Information from Existing Technologies.

Degree: Computer Science, 2015, University of North Carolina

 The use of genotyping and sequencing technologies in genetic studies typically involves inspecting variants defined within a single reference genome. While this definition of genetic… (more)

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

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

APA (6th Edition):

Fu, C. (2015). Analysis of Admixed Animals using Indirect Haplotype Information from Existing Technologies. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:087b876d-f949-4963-929f-84444e9bf85f

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):

Fu, Chen-Ping. “Analysis of Admixed Animals using Indirect Haplotype Information from Existing Technologies.” 2015. Thesis, University of North Carolina. Accessed November 29, 2020. https://cdr.lib.unc.edu/record/uuid:087b876d-f949-4963-929f-84444e9bf85f.

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

MLA Handbook (7th Edition):

Fu, Chen-Ping. “Analysis of Admixed Animals using Indirect Haplotype Information from Existing Technologies.” 2015. Web. 29 Nov 2020.

Vancouver:

Fu C. Analysis of Admixed Animals using Indirect Haplotype Information from Existing Technologies. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2020 Nov 29]. Available from: https://cdr.lib.unc.edu/record/uuid:087b876d-f949-4963-929f-84444e9bf85f.

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

Council of Science Editors:

Fu C. Analysis of Admixed Animals using Indirect Haplotype Information from Existing Technologies. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:087b876d-f949-4963-929f-84444e9bf85f

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


University of North Carolina

8. YANG, SHAN. NON-RIGID BODY MECHANICAL PROPERTY RECOVERY FROM IMAGES AND VIDEOS.

Degree: Computer Science, 2018, University of North Carolina

 Material property has great importance in surgical simulation and virtual reality. The mechanical properties of the human soft tissue are critical to characterize the tissue… (more)

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

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

APA (6th Edition):

YANG, S. (2018). NON-RIGID BODY MECHANICAL PROPERTY RECOVERY FROM IMAGES AND VIDEOS. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:7841341b-857a-4e7d-9872-05d23b63e56d

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):

YANG, SHAN. “NON-RIGID BODY MECHANICAL PROPERTY RECOVERY FROM IMAGES AND VIDEOS.” 2018. Thesis, University of North Carolina. Accessed November 29, 2020. https://cdr.lib.unc.edu/record/uuid:7841341b-857a-4e7d-9872-05d23b63e56d.

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

MLA Handbook (7th Edition):

YANG, SHAN. “NON-RIGID BODY MECHANICAL PROPERTY RECOVERY FROM IMAGES AND VIDEOS.” 2018. Web. 29 Nov 2020.

Vancouver:

YANG S. NON-RIGID BODY MECHANICAL PROPERTY RECOVERY FROM IMAGES AND VIDEOS. [Internet] [Thesis]. University of North Carolina; 2018. [cited 2020 Nov 29]. Available from: https://cdr.lib.unc.edu/record/uuid:7841341b-857a-4e7d-9872-05d23b63e56d.

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

Council of Science Editors:

YANG S. NON-RIGID BODY MECHANICAL PROPERTY RECOVERY FROM IMAGES AND VIDEOS. [Thesis]. University of North Carolina; 2018. Available from: https://cdr.lib.unc.edu/record/uuid:7841341b-857a-4e7d-9872-05d23b63e56d

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


University of North Carolina

9. Holt, James. USING THE MULTI-STRING BURROW-WHEELER TRANSFORM FOR HIGH-THROUGHPUT SEQUENCE ANALYSIS.

Degree: Computer Science, 2016, University of North Carolina

 The throughput of sequencing technologies has created a bottleneck where raw sequence files are stored in an un-indexed format on disk. Alignment to a reference… (more)

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

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

APA (6th Edition):

Holt, J. (2016). USING THE MULTI-STRING BURROW-WHEELER TRANSFORM FOR HIGH-THROUGHPUT SEQUENCE ANALYSIS. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:2dd1d367-ba4b-4cdb-a4ff-30063b519b43

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):

Holt, James. “USING THE MULTI-STRING BURROW-WHEELER TRANSFORM FOR HIGH-THROUGHPUT SEQUENCE ANALYSIS.” 2016. Thesis, University of North Carolina. Accessed November 29, 2020. https://cdr.lib.unc.edu/record/uuid:2dd1d367-ba4b-4cdb-a4ff-30063b519b43.

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

MLA Handbook (7th Edition):

Holt, James. “USING THE MULTI-STRING BURROW-WHEELER TRANSFORM FOR HIGH-THROUGHPUT SEQUENCE ANALYSIS.” 2016. Web. 29 Nov 2020.

Vancouver:

Holt J. USING THE MULTI-STRING BURROW-WHEELER TRANSFORM FOR HIGH-THROUGHPUT SEQUENCE ANALYSIS. [Internet] [Thesis]. University of North Carolina; 2016. [cited 2020 Nov 29]. Available from: https://cdr.lib.unc.edu/record/uuid:2dd1d367-ba4b-4cdb-a4ff-30063b519b43.

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

Council of Science Editors:

Holt J. USING THE MULTI-STRING BURROW-WHEELER TRANSFORM FOR HIGH-THROUGHPUT SEQUENCE ANALYSIS. [Thesis]. University of North Carolina; 2016. Available from: https://cdr.lib.unc.edu/record/uuid:2dd1d367-ba4b-4cdb-a4ff-30063b519b43

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


University of North Carolina

10. Zhang, Zhaojun. Efficient Computational Genetics Methods for Multiparent Crosses.

Degree: Computer Science, 2014, University of North Carolina

 Multiparent crosses are genetic populations bred in a controlled manner from a finite number of known founders. They represent experimental resources that are of potentially… (more)

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

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

APA (6th Edition):

Zhang, Z. (2014). Efficient Computational Genetics Methods for Multiparent Crosses. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:81496805-1c98-4416-a013-efb7fba8ee15

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

Chicago Manual of Style (16th Edition):

Zhang, Zhaojun. “Efficient Computational Genetics Methods for Multiparent Crosses.” 2014. Thesis, University of North Carolina. Accessed November 29, 2020. https://cdr.lib.unc.edu/record/uuid:81496805-1c98-4416-a013-efb7fba8ee15.

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

MLA Handbook (7th Edition):

Zhang, Zhaojun. “Efficient Computational Genetics Methods for Multiparent Crosses.” 2014. Web. 29 Nov 2020.

Vancouver:

Zhang Z. Efficient Computational Genetics Methods for Multiparent Crosses. [Internet] [Thesis]. University of North Carolina; 2014. [cited 2020 Nov 29]. Available from: https://cdr.lib.unc.edu/record/uuid:81496805-1c98-4416-a013-efb7fba8ee15.

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

Council of Science Editors:

Zhang Z. Efficient Computational Genetics Methods for Multiparent Crosses. [Thesis]. University of North Carolina; 2014. Available from: https://cdr.lib.unc.edu/record/uuid:81496805-1c98-4416-a013-efb7fba8ee15

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


University of North Carolina

11. Kao, Chia-Yu. A Deep Learning Architecture For Histology Image Classification.

Degree: Computer Science, 2018, University of North Carolina

 Over the past decade, a machine learning technique called deep-learning has gained prominence in computer vision because of its ability to extract semantics from natural… (more)

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

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

APA (6th Edition):

Kao, C. (2018). A Deep Learning Architecture For Histology Image Classification. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:363beb32-6a94-43ff-9540-baf14d36ec56

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):

Kao, Chia-Yu. “A Deep Learning Architecture For Histology Image Classification.” 2018. Thesis, University of North Carolina. Accessed November 29, 2020. https://cdr.lib.unc.edu/record/uuid:363beb32-6a94-43ff-9540-baf14d36ec56.

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

MLA Handbook (7th Edition):

Kao, Chia-Yu. “A Deep Learning Architecture For Histology Image Classification.” 2018. Web. 29 Nov 2020.

Vancouver:

Kao C. A Deep Learning Architecture For Histology Image Classification. [Internet] [Thesis]. University of North Carolina; 2018. [cited 2020 Nov 29]. Available from: https://cdr.lib.unc.edu/record/uuid:363beb32-6a94-43ff-9540-baf14d36ec56.

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

Council of Science Editors:

Kao C. A Deep Learning Architecture For Histology Image Classification. [Thesis]. University of North Carolina; 2018. Available from: https://cdr.lib.unc.edu/record/uuid:363beb32-6a94-43ff-9540-baf14d36ec56

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

.