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You searched for subject:(Image segmentation). Showing records 1 – 30 of 1278 total matches.

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1. Kouzana, Amira. Conception d'un cadre d'optimisation de fonctions d'énergies : application au traitement d'images : New framework design for optimizing energy functions : application to image processing.

Degree: Docteur es, Signal, Image, Automatique, 2018, Université Paris-Est

Nous proposons une nouvelle formulation de minimisation de fonctions d’énergies pour la traitement de la vision sur toute la segmentation d'image. Le problème est modélisé… (more)

Subjects/Keywords: Image; Optimisation; Segmentation; Image; Optimization; Segmentation

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

APA (6th Edition):

Kouzana, A. (2018). Conception d'un cadre d'optimisation de fonctions d'énergies : application au traitement d'images : New framework design for optimizing energy functions : application to image processing. (Doctoral Dissertation). Université Paris-Est. Retrieved from http://www.theses.fr/2018PESC1121

Chicago Manual of Style (16th Edition):

Kouzana, Amira. “Conception d'un cadre d'optimisation de fonctions d'énergies : application au traitement d'images : New framework design for optimizing energy functions : application to image processing.” 2018. Doctoral Dissertation, Université Paris-Est. Accessed March 01, 2021. http://www.theses.fr/2018PESC1121.

MLA Handbook (7th Edition):

Kouzana, Amira. “Conception d'un cadre d'optimisation de fonctions d'énergies : application au traitement d'images : New framework design for optimizing energy functions : application to image processing.” 2018. Web. 01 Mar 2021.

Vancouver:

Kouzana A. Conception d'un cadre d'optimisation de fonctions d'énergies : application au traitement d'images : New framework design for optimizing energy functions : application to image processing. [Internet] [Doctoral dissertation]. Université Paris-Est; 2018. [cited 2021 Mar 01]. Available from: http://www.theses.fr/2018PESC1121.

Council of Science Editors:

Kouzana A. Conception d'un cadre d'optimisation de fonctions d'énergies : application au traitement d'images : New framework design for optimizing energy functions : application to image processing. [Doctoral Dissertation]. Université Paris-Est; 2018. Available from: http://www.theses.fr/2018PESC1121


Oregon State University

2. Chen, Sheng. Object Tracking-by-Segmentation in Videos.

Degree: PhD, Computer Science, 2017, Oregon State University

 This thesis focuses on the problem of object tracking. Given a video, the general objective of tracking is to track the location over time of… (more)

Subjects/Keywords: Tracking; Image segmentation

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APA (6th Edition):

Chen, S. (2017). Object Tracking-by-Segmentation in Videos. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/60452

Chicago Manual of Style (16th Edition):

Chen, Sheng. “Object Tracking-by-Segmentation in Videos.” 2017. Doctoral Dissertation, Oregon State University. Accessed March 01, 2021. http://hdl.handle.net/1957/60452.

MLA Handbook (7th Edition):

Chen, Sheng. “Object Tracking-by-Segmentation in Videos.” 2017. Web. 01 Mar 2021.

Vancouver:

Chen S. Object Tracking-by-Segmentation in Videos. [Internet] [Doctoral dissertation]. Oregon State University; 2017. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/1957/60452.

Council of Science Editors:

Chen S. Object Tracking-by-Segmentation in Videos. [Doctoral Dissertation]. Oregon State University; 2017. Available from: http://hdl.handle.net/1957/60452


University of Missouri – Columbia

3. Meena, Sachin, 1981-. Elastic map: interactive image segmentation using a few seed-points.

Degree: 2016, University of Missouri – Columbia

 Over the past two decades interactive methods for clinical and biomedical image segmentation have been investigated since the pioneering work of Live-Wire, Live-Lane [17] and… (more)

Subjects/Keywords: Image segmentation; Splines

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APA (6th Edition):

Meena, Sachin, 1. (2016). Elastic map: interactive image segmentation using a few seed-points. (Thesis). University of Missouri – Columbia. Retrieved from https://doi.org/10.32469/10355/57241

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):

Meena, Sachin, 1981-. “Elastic map: interactive image segmentation using a few seed-points.” 2016. Thesis, University of Missouri – Columbia. Accessed March 01, 2021. https://doi.org/10.32469/10355/57241.

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

MLA Handbook (7th Edition):

Meena, Sachin, 1981-. “Elastic map: interactive image segmentation using a few seed-points.” 2016. Web. 01 Mar 2021.

Vancouver:

Meena, Sachin 1. Elastic map: interactive image segmentation using a few seed-points. [Internet] [Thesis]. University of Missouri – Columbia; 2016. [cited 2021 Mar 01]. Available from: https://doi.org/10.32469/10355/57241.

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

Council of Science Editors:

Meena, Sachin 1. Elastic map: interactive image segmentation using a few seed-points. [Thesis]. University of Missouri – Columbia; 2016. Available from: https://doi.org/10.32469/10355/57241

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


Penn State University

4. Zang, Xiaonan. Ebus/ct Fusion for Image-guided Bronchoscopy.

Degree: 2016, Penn State University

 Many technical innovations in multimodal radiologic imaging and bronchoscopy have arisen to improve lung-cancer staging techniques. Among the innovations, endobronchial ultrasound (EBUS), which provides live… (more)

Subjects/Keywords: image segmentation; image registration; ultrasound

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APA (6th Edition):

Zang, X. (2016). Ebus/ct Fusion for Image-guided Bronchoscopy. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/28651

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):

Zang, Xiaonan. “Ebus/ct Fusion for Image-guided Bronchoscopy.” 2016. Thesis, Penn State University. Accessed March 01, 2021. https://submit-etda.libraries.psu.edu/catalog/28651.

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

MLA Handbook (7th Edition):

Zang, Xiaonan. “Ebus/ct Fusion for Image-guided Bronchoscopy.” 2016. Web. 01 Mar 2021.

Vancouver:

Zang X. Ebus/ct Fusion for Image-guided Bronchoscopy. [Internet] [Thesis]. Penn State University; 2016. [cited 2021 Mar 01]. Available from: https://submit-etda.libraries.psu.edu/catalog/28651.

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

Council of Science Editors:

Zang X. Ebus/ct Fusion for Image-guided Bronchoscopy. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/28651

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


Rochester Institute of Technology

5. Hayes, Tyler L. Compassionately Conservative Normalized Cuts for Image Segmentation.

Degree: MS, School of Mathematical Sciences (COS), 2017, Rochester Institute of Technology

Image segmentation is a process used in computer vision to partition an image into regions with similar characteristics. One category of image segmentation algorithms… (more)

Subjects/Keywords: Graph-based segmentation; Image segmentation; Optimization

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APA (6th Edition):

Hayes, T. L. (2017). Compassionately Conservative Normalized Cuts for Image Segmentation. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9409

Chicago Manual of Style (16th Edition):

Hayes, Tyler L. “Compassionately Conservative Normalized Cuts for Image Segmentation.” 2017. Masters Thesis, Rochester Institute of Technology. Accessed March 01, 2021. https://scholarworks.rit.edu/theses/9409.

MLA Handbook (7th Edition):

Hayes, Tyler L. “Compassionately Conservative Normalized Cuts for Image Segmentation.” 2017. Web. 01 Mar 2021.

Vancouver:

Hayes TL. Compassionately Conservative Normalized Cuts for Image Segmentation. [Internet] [Masters thesis]. Rochester Institute of Technology; 2017. [cited 2021 Mar 01]. Available from: https://scholarworks.rit.edu/theses/9409.

Council of Science Editors:

Hayes TL. Compassionately Conservative Normalized Cuts for Image Segmentation. [Masters Thesis]. Rochester Institute of Technology; 2017. Available from: https://scholarworks.rit.edu/theses/9409


Carnegie Mellon University

6. Woods, Bronwyn Lewisia. Toward a Processing Pipeline for Two-photon Calcium Imaging of Neural Populations.

Degree: 2013, Carnegie Mellon University

 Two-photon calcium imaging (TPCI) is a functional neuroimaging technique that simultaneously reveals the function of small populations of cells as well as the structure of… (more)

Subjects/Keywords: neuroimagining; image segmentation; motion correction

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APA (6th Edition):

Woods, B. L. (2013). Toward a Processing Pipeline for Two-photon Calcium Imaging of Neural Populations. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/393

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):

Woods, Bronwyn Lewisia. “Toward a Processing Pipeline for Two-photon Calcium Imaging of Neural Populations.” 2013. Thesis, Carnegie Mellon University. Accessed March 01, 2021. http://repository.cmu.edu/dissertations/393.

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

MLA Handbook (7th Edition):

Woods, Bronwyn Lewisia. “Toward a Processing Pipeline for Two-photon Calcium Imaging of Neural Populations.” 2013. Web. 01 Mar 2021.

Vancouver:

Woods BL. Toward a Processing Pipeline for Two-photon Calcium Imaging of Neural Populations. [Internet] [Thesis]. Carnegie Mellon University; 2013. [cited 2021 Mar 01]. Available from: http://repository.cmu.edu/dissertations/393.

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

Council of Science Editors:

Woods BL. Toward a Processing Pipeline for Two-photon Calcium Imaging of Neural Populations. [Thesis]. Carnegie Mellon University; 2013. Available from: http://repository.cmu.edu/dissertations/393

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


University of Alberta

7. Wang, Hui. Shape-Guided Interactive Image Segmentation.

Degree: PhD, Department of Computing Science, 2012, University of Alberta

 This dissertation contributes to developing shape-guided algorithms for interactive image segmentation. Prior knowledge which describes what is expected in an image is the key to… (more)

Subjects/Keywords: interactive image segmentation; shape prior

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

APA (6th Edition):

Wang, H. (2012). Shape-Guided Interactive Image Segmentation. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/7p88cg94m

Chicago Manual of Style (16th Edition):

Wang, Hui. “Shape-Guided Interactive Image Segmentation.” 2012. Doctoral Dissertation, University of Alberta. Accessed March 01, 2021. https://era.library.ualberta.ca/files/7p88cg94m.

MLA Handbook (7th Edition):

Wang, Hui. “Shape-Guided Interactive Image Segmentation.” 2012. Web. 01 Mar 2021.

Vancouver:

Wang H. Shape-Guided Interactive Image Segmentation. [Internet] [Doctoral dissertation]. University of Alberta; 2012. [cited 2021 Mar 01]. Available from: https://era.library.ualberta.ca/files/7p88cg94m.

Council of Science Editors:

Wang H. Shape-Guided Interactive Image Segmentation. [Doctoral Dissertation]. University of Alberta; 2012. Available from: https://era.library.ualberta.ca/files/7p88cg94m

8. Zulaikha beevi, S. Study of medical image segmentation algorithms;.

Degree: 2015, Manonmaniam Sundaranar University

in image analysis segmentation is the partitioning of a digital image into multiple regions newlinesets of pixels according to some homogeneity criterion the problem of… (more)

Subjects/Keywords: algorithms; image; medical; segmentation

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APA (6th Edition):

Zulaikha beevi, S. (2015). Study of medical image segmentation algorithms;. (Thesis). Manonmaniam Sundaranar University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/38398

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):

Zulaikha beevi, S. “Study of medical image segmentation algorithms;.” 2015. Thesis, Manonmaniam Sundaranar University. Accessed March 01, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/38398.

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

MLA Handbook (7th Edition):

Zulaikha beevi, S. “Study of medical image segmentation algorithms;.” 2015. Web. 01 Mar 2021.

Vancouver:

Zulaikha beevi S. Study of medical image segmentation algorithms;. [Internet] [Thesis]. Manonmaniam Sundaranar University; 2015. [cited 2021 Mar 01]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/38398.

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

Council of Science Editors:

Zulaikha beevi S. Study of medical image segmentation algorithms;. [Thesis]. Manonmaniam Sundaranar University; 2015. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/38398

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


Baylor University

9. Nguyen, Hanh Hong, 1991-. Automated medical image segmentation.

Degree: M.S.B.M.E., Baylor University. Dept. of Electrical & Computer Engineering., 2017, Baylor University

 Computed Tomography (CT) is one of the most common medical diagnostic imaging techniques. Since the first clinical CT scanner was installed in the 1970s, there… (more)

Subjects/Keywords: Medical image. Auto segmentation.

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APA (6th Edition):

Nguyen, Hanh Hong, 1. (2017). Automated medical image segmentation. (Masters Thesis). Baylor University. Retrieved from http://hdl.handle.net/2104/10195

Chicago Manual of Style (16th Edition):

Nguyen, Hanh Hong, 1991-. “Automated medical image segmentation.” 2017. Masters Thesis, Baylor University. Accessed March 01, 2021. http://hdl.handle.net/2104/10195.

MLA Handbook (7th Edition):

Nguyen, Hanh Hong, 1991-. “Automated medical image segmentation.” 2017. Web. 01 Mar 2021.

Vancouver:

Nguyen, Hanh Hong 1. Automated medical image segmentation. [Internet] [Masters thesis]. Baylor University; 2017. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/2104/10195.

Council of Science Editors:

Nguyen, Hanh Hong 1. Automated medical image segmentation. [Masters Thesis]. Baylor University; 2017. Available from: http://hdl.handle.net/2104/10195


University of Florida

10. Xing, Fuyong. High-throughput Biomedical Image Computing for Digital Health.

Degree: PhD, Electrical and Computer Engineering, 2017, University of Florida

 In biomedical informatics, a large amount of image data has been collected to support clinical diagnosis, treatment decision, and medical prognosis. The large volume and… (more)

Subjects/Keywords: cell  – detection  – image  – nucleus  – segmentation

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APA (6th Edition):

Xing, F. (2017). High-throughput Biomedical Image Computing for Digital Health. (Doctoral Dissertation). University of Florida. Retrieved from https://ufdc.ufl.edu/UFE0051289

Chicago Manual of Style (16th Edition):

Xing, Fuyong. “High-throughput Biomedical Image Computing for Digital Health.” 2017. Doctoral Dissertation, University of Florida. Accessed March 01, 2021. https://ufdc.ufl.edu/UFE0051289.

MLA Handbook (7th Edition):

Xing, Fuyong. “High-throughput Biomedical Image Computing for Digital Health.” 2017. Web. 01 Mar 2021.

Vancouver:

Xing F. High-throughput Biomedical Image Computing for Digital Health. [Internet] [Doctoral dissertation]. University of Florida; 2017. [cited 2021 Mar 01]. Available from: https://ufdc.ufl.edu/UFE0051289.

Council of Science Editors:

Xing F. High-throughput Biomedical Image Computing for Digital Health. [Doctoral Dissertation]. University of Florida; 2017. Available from: https://ufdc.ufl.edu/UFE0051289


University of Waterloo

11. Sahba, Farhang. Reinforced Segmentation of Images Containing One Object of Interest.

Degree: 2007, University of Waterloo

 In many image-processing applications, one object of interest must be segmented. The techniques used for segmentation vary depending on the particular situation and the specifications… (more)

Subjects/Keywords: Image Segmentation

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APA (6th Edition):

Sahba, F. (2007). Reinforced Segmentation of Images Containing One Object of Interest. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/3420

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):

Sahba, Farhang. “Reinforced Segmentation of Images Containing One Object of Interest.” 2007. Thesis, University of Waterloo. Accessed March 01, 2021. http://hdl.handle.net/10012/3420.

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

MLA Handbook (7th Edition):

Sahba, Farhang. “Reinforced Segmentation of Images Containing One Object of Interest.” 2007. Web. 01 Mar 2021.

Vancouver:

Sahba F. Reinforced Segmentation of Images Containing One Object of Interest. [Internet] [Thesis]. University of Waterloo; 2007. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/10012/3420.

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

Council of Science Editors:

Sahba F. Reinforced Segmentation of Images Containing One Object of Interest. [Thesis]. University of Waterloo; 2007. Available from: http://hdl.handle.net/10012/3420

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


Vanderbilt University

12. Plassard, Andrew John. Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson’s Disease.

Degree: PhD, Computer Science, 2017, Vanderbilt University

 Improved segmentation of magnetic resonance imaging is necessary to provide quantitative and anatomical information for current and future radiological understanding of Parkinson’s disease and progression.… (more)

Subjects/Keywords: Medical Image Segmentation; Parkinson's disease

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APA (6th Edition):

Plassard, A. J. (2017). Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson’s Disease. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14512

Chicago Manual of Style (16th Edition):

Plassard, Andrew John. “Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson’s Disease.” 2017. Doctoral Dissertation, Vanderbilt University. Accessed March 01, 2021. http://hdl.handle.net/1803/14512.

MLA Handbook (7th Edition):

Plassard, Andrew John. “Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson’s Disease.” 2017. Web. 01 Mar 2021.

Vancouver:

Plassard AJ. Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson’s Disease. [Internet] [Doctoral dissertation]. Vanderbilt University; 2017. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/1803/14512.

Council of Science Editors:

Plassard AJ. Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson’s Disease. [Doctoral Dissertation]. Vanderbilt University; 2017. Available from: http://hdl.handle.net/1803/14512


Rutgers University

13. Senlet, Turgay, 1981-. Visual localization, semantic video segmentation and labeling using satellite maps.

Degree: PhD, Computer Science, 2015, Rutgers University

In this dissertation, I propose vision-based geo-localization and segmentation methods that make use of semantic and appearance information from satellite images. First, I present a… (more)

Subjects/Keywords: Image segmentation; Visual perception

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APA (6th Edition):

Senlet, Turgay, 1. (2015). Visual localization, semantic video segmentation and labeling using satellite maps. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/47583/

Chicago Manual of Style (16th Edition):

Senlet, Turgay, 1981-. “Visual localization, semantic video segmentation and labeling using satellite maps.” 2015. Doctoral Dissertation, Rutgers University. Accessed March 01, 2021. https://rucore.libraries.rutgers.edu/rutgers-lib/47583/.

MLA Handbook (7th Edition):

Senlet, Turgay, 1981-. “Visual localization, semantic video segmentation and labeling using satellite maps.” 2015. Web. 01 Mar 2021.

Vancouver:

Senlet, Turgay 1. Visual localization, semantic video segmentation and labeling using satellite maps. [Internet] [Doctoral dissertation]. Rutgers University; 2015. [cited 2021 Mar 01]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/47583/.

Council of Science Editors:

Senlet, Turgay 1. Visual localization, semantic video segmentation and labeling using satellite maps. [Doctoral Dissertation]. Rutgers University; 2015. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/47583/


University of Minnesota

14. Li, Peng. FPGA-based hardware implementation of image processing algorithms for real-time vehicle detection applications.

Degree: MS, Electrical/Computer Engineering, 2012, University of Minnesota

University of Minnesota M.S. thesis. October 2012. Major: Electrical/Computer Engineering. Advisor: Hua Tang. 1 computer file (PDF); viii, 47 pages, appendix A.

It is well… (more)

Subjects/Keywords: FPGA; Image processing; Image segmentation; VLSI

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APA (6th Edition):

Li, P. (2012). FPGA-based hardware implementation of image processing algorithms for real-time vehicle detection applications. (Masters Thesis). University of Minnesota. Retrieved from http://purl.umn.edu/140237

Chicago Manual of Style (16th Edition):

Li, Peng. “FPGA-based hardware implementation of image processing algorithms for real-time vehicle detection applications.” 2012. Masters Thesis, University of Minnesota. Accessed March 01, 2021. http://purl.umn.edu/140237.

MLA Handbook (7th Edition):

Li, Peng. “FPGA-based hardware implementation of image processing algorithms for real-time vehicle detection applications.” 2012. Web. 01 Mar 2021.

Vancouver:

Li P. FPGA-based hardware implementation of image processing algorithms for real-time vehicle detection applications. [Internet] [Masters thesis]. University of Minnesota; 2012. [cited 2021 Mar 01]. Available from: http://purl.umn.edu/140237.

Council of Science Editors:

Li P. FPGA-based hardware implementation of image processing algorithms for real-time vehicle detection applications. [Masters Thesis]. University of Minnesota; 2012. Available from: http://purl.umn.edu/140237


University of Alberta

15. Popuri, Karteek. A unified FEM-based framework for medical image registration and segmentation.

Degree: PhD, Department of Computing Science, 2013, University of Alberta

 Medical image registration and segmentation are challenging because, medical images are generally corrupted by noise, image artifacts and the various anatomical regions of interest in… (more)

Subjects/Keywords: Finite element method; Image registration; Image segmentation

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APA (6th Edition):

Popuri, K. (2013). A unified FEM-based framework for medical image registration and segmentation. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/0z708w85q

Chicago Manual of Style (16th Edition):

Popuri, Karteek. “A unified FEM-based framework for medical image registration and segmentation.” 2013. Doctoral Dissertation, University of Alberta. Accessed March 01, 2021. https://era.library.ualberta.ca/files/0z708w85q.

MLA Handbook (7th Edition):

Popuri, Karteek. “A unified FEM-based framework for medical image registration and segmentation.” 2013. Web. 01 Mar 2021.

Vancouver:

Popuri K. A unified FEM-based framework for medical image registration and segmentation. [Internet] [Doctoral dissertation]. University of Alberta; 2013. [cited 2021 Mar 01]. Available from: https://era.library.ualberta.ca/files/0z708w85q.

Council of Science Editors:

Popuri K. A unified FEM-based framework for medical image registration and segmentation. [Doctoral Dissertation]. University of Alberta; 2013. Available from: https://era.library.ualberta.ca/files/0z708w85q


Hong Kong University of Science and Technology

16. Zhen, Mingmin CSE. Learning discriminative representation for pixel-wise recognition.

Degree: 2020, Hong Kong University of Science and Technology

 Pixel-wise recognition tasks, including semantic segmentation, salient object detection, and unsupervised video object segmentation in this thesis, aim to classify each pixel (point) of the… (more)

Subjects/Keywords: Image processing ; Mathematical models ; Image segmentation

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APA (6th Edition):

Zhen, M. C. (2020). Learning discriminative representation for pixel-wise recognition. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-105567 ; https://doi.org/10.14711/thesis-991012862969803412 ; http://repository.ust.hk/ir/bitstream/1783.1-105567/1/th_redirect.html

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):

Zhen, Mingmin CSE. “Learning discriminative representation for pixel-wise recognition.” 2020. Thesis, Hong Kong University of Science and Technology. Accessed March 01, 2021. http://repository.ust.hk/ir/Record/1783.1-105567 ; https://doi.org/10.14711/thesis-991012862969803412 ; http://repository.ust.hk/ir/bitstream/1783.1-105567/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Zhen, Mingmin CSE. “Learning discriminative representation for pixel-wise recognition.” 2020. Web. 01 Mar 2021.

Vancouver:

Zhen MC. Learning discriminative representation for pixel-wise recognition. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2020. [cited 2021 Mar 01]. Available from: http://repository.ust.hk/ir/Record/1783.1-105567 ; https://doi.org/10.14711/thesis-991012862969803412 ; http://repository.ust.hk/ir/bitstream/1783.1-105567/1/th_redirect.html.

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

Council of Science Editors:

Zhen MC. Learning discriminative representation for pixel-wise recognition. [Thesis]. Hong Kong University of Science and Technology; 2020. Available from: http://repository.ust.hk/ir/Record/1783.1-105567 ; https://doi.org/10.14711/thesis-991012862969803412 ; http://repository.ust.hk/ir/bitstream/1783.1-105567/1/th_redirect.html

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


University of Ontario Institute of Technology

17. Darvish, Arman. User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation.

Degree: 2011, University of Ontario Institute of Technology

 Applications of imaging and image processing become a part of our daily life and find their crucial way in real-world areas. Accordingly, the corresponding techniques… (more)

Subjects/Keywords: Image processing; Segmentation; Optimization; Image enhancement

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

APA (6th Edition):

Darvish, A. (2011). User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/209

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):

Darvish, Arman. “User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation.” 2011. Thesis, University of Ontario Institute of Technology. Accessed March 01, 2021. http://hdl.handle.net/10155/209.

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

MLA Handbook (7th Edition):

Darvish, Arman. “User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation.” 2011. Web. 01 Mar 2021.

Vancouver:

Darvish A. User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation. [Internet] [Thesis]. University of Ontario Institute of Technology; 2011. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/10155/209.

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

Council of Science Editors:

Darvish A. User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation. [Thesis]. University of Ontario Institute of Technology; 2011. Available from: http://hdl.handle.net/10155/209

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


Rutgers University

18. Uzunbas, Mustafa Gokhan, 1983-. Automatic and interactive segmentations using deformable and graphical models.

Degree: PhD, Computer Science, 2015, Rutgers University

Image segmentation i.e. dividing an image into regions and categories is a classic yet still challenging problem. The key to success is to use/develop the… (more)

Subjects/Keywords: Image segmentation; Image analysis; Electron microscopy

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APA (6th Edition):

Uzunbas, Mustafa Gokhan, 1. (2015). Automatic and interactive segmentations using deformable and graphical models. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/46449/

Chicago Manual of Style (16th Edition):

Uzunbas, Mustafa Gokhan, 1983-. “Automatic and interactive segmentations using deformable and graphical models.” 2015. Doctoral Dissertation, Rutgers University. Accessed March 01, 2021. https://rucore.libraries.rutgers.edu/rutgers-lib/46449/.

MLA Handbook (7th Edition):

Uzunbas, Mustafa Gokhan, 1983-. “Automatic and interactive segmentations using deformable and graphical models.” 2015. Web. 01 Mar 2021.

Vancouver:

Uzunbas, Mustafa Gokhan 1. Automatic and interactive segmentations using deformable and graphical models. [Internet] [Doctoral dissertation]. Rutgers University; 2015. [cited 2021 Mar 01]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/46449/.

Council of Science Editors:

Uzunbas, Mustafa Gokhan 1. Automatic and interactive segmentations using deformable and graphical models. [Doctoral Dissertation]. Rutgers University; 2015. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/46449/

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

Degree: PhD, Computer Science, 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. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63453

Chicago Manual of Style (16th Edition):

Jain, Suyog Dutt. “Human machine collaboration for foreground segmentation in images and videos.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed March 01, 2021. http://hdl.handle.net/2152/63453.

MLA Handbook (7th Edition):

Jain, Suyog Dutt. “Human machine collaboration for foreground segmentation in images and videos.” 2018. Web. 01 Mar 2021.

Vancouver:

Jain SD. Human machine collaboration for foreground segmentation in images and videos. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/2152/63453.

Council of Science Editors:

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


Northeastern University

20. Golabchi, Fatemeh Noushin. Graphical model based segmentation of massive numbers of irregular small objects in images, with application to axon characterization in histological sections.

Degree: PhD, Department of Electrical and Computer Engineering, 2013, Northeastern University

Segmentation and classification of images into desired components is a fundamental problem in biomedical image processing. In this work we address the particular problem of… (more)

Subjects/Keywords: Axon Segmentation; Histology Images; Image Segmentation; Microscopy Image Segmentation; Model based Image Segmentation; Probabilistic Graphical Models; Biomedical; Electrical and Computer Engineering

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

APA (6th Edition):

Golabchi, F. N. (2013). Graphical model based segmentation of massive numbers of irregular small objects in images, with application to axon characterization in histological sections. (Doctoral Dissertation). Northeastern University. Retrieved from http://hdl.handle.net/2047/d20004837

Chicago Manual of Style (16th Edition):

Golabchi, Fatemeh Noushin. “Graphical model based segmentation of massive numbers of irregular small objects in images, with application to axon characterization in histological sections.” 2013. Doctoral Dissertation, Northeastern University. Accessed March 01, 2021. http://hdl.handle.net/2047/d20004837.

MLA Handbook (7th Edition):

Golabchi, Fatemeh Noushin. “Graphical model based segmentation of massive numbers of irregular small objects in images, with application to axon characterization in histological sections.” 2013. Web. 01 Mar 2021.

Vancouver:

Golabchi FN. Graphical model based segmentation of massive numbers of irregular small objects in images, with application to axon characterization in histological sections. [Internet] [Doctoral dissertation]. Northeastern University; 2013. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/2047/d20004837.

Council of Science Editors:

Golabchi FN. Graphical model based segmentation of massive numbers of irregular small objects in images, with application to axon characterization in histological sections. [Doctoral Dissertation]. Northeastern University; 2013. Available from: http://hdl.handle.net/2047/d20004837


Brigham Young University

21. Price, Brian L. Interactive Object Selection and Matting for Video and Images.

Degree: PhD, 2010, Brigham Young University

 Video segmentation, the process of selecting an object out of a video sequence, is a fundamentally important process for video editing and special effects. However,… (more)

Subjects/Keywords: video segmentation; image segmentation; image matting; color modeling; Computer Sciences

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

APA (6th Edition):

Price, B. L. (2010). Interactive Object Selection and Matting for Video and Images. (Doctoral Dissertation). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3593&context=etd

Chicago Manual of Style (16th Edition):

Price, Brian L. “Interactive Object Selection and Matting for Video and Images.” 2010. Doctoral Dissertation, Brigham Young University. Accessed March 01, 2021. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3593&context=etd.

MLA Handbook (7th Edition):

Price, Brian L. “Interactive Object Selection and Matting for Video and Images.” 2010. Web. 01 Mar 2021.

Vancouver:

Price BL. Interactive Object Selection and Matting for Video and Images. [Internet] [Doctoral dissertation]. Brigham Young University; 2010. [cited 2021 Mar 01]. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3593&context=etd.

Council of Science Editors:

Price BL. Interactive Object Selection and Matting for Video and Images. [Doctoral Dissertation]. Brigham Young University; 2010. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3593&context=etd

22. Sekkal, Rafiq. Techniques visuelles pour la détection et le suivi d’objets 2D : Visual techniques for 2D object detection and tracking.

Degree: Docteur es, Traitement du signal et de l'image, 2014, Rennes, INSA

De nos jours, le traitement et l’analyse d’images trouvent leur application dans de nombreux domaines. Dans le cas de la navigation d’un robot mobile (fauteuil… (more)

Subjects/Keywords: Segmentation d'images; Segmentation spatiotemporelle; Techniques de détection; Image segmentation; Spatiotemporal segmentation; Detection technique; 621

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

APA (6th Edition):

Sekkal, R. (2014). Techniques visuelles pour la détection et le suivi d’objets 2D : Visual techniques for 2D object detection and tracking. (Doctoral Dissertation). Rennes, INSA. Retrieved from http://www.theses.fr/2014ISAR0032

Chicago Manual of Style (16th Edition):

Sekkal, Rafiq. “Techniques visuelles pour la détection et le suivi d’objets 2D : Visual techniques for 2D object detection and tracking.” 2014. Doctoral Dissertation, Rennes, INSA. Accessed March 01, 2021. http://www.theses.fr/2014ISAR0032.

MLA Handbook (7th Edition):

Sekkal, Rafiq. “Techniques visuelles pour la détection et le suivi d’objets 2D : Visual techniques for 2D object detection and tracking.” 2014. Web. 01 Mar 2021.

Vancouver:

Sekkal R. Techniques visuelles pour la détection et le suivi d’objets 2D : Visual techniques for 2D object detection and tracking. [Internet] [Doctoral dissertation]. Rennes, INSA; 2014. [cited 2021 Mar 01]. Available from: http://www.theses.fr/2014ISAR0032.

Council of Science Editors:

Sekkal R. Techniques visuelles pour la détection et le suivi d’objets 2D : Visual techniques for 2D object detection and tracking. [Doctoral Dissertation]. Rennes, INSA; 2014. Available from: http://www.theses.fr/2014ISAR0032


University of Bridgeport

23. Almotiri, Jasem. A Multi-Anatomical Retinal Structure Segmentation System For Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding .

Degree: 2018, University of Bridgeport

 Eye exam can be as efficacious as physical one in determining health concerns. Retina screening can be the very first clue to detecting a variety… (more)

Subjects/Keywords: Fuzzy systems; Image segmentation; Optic disc segmentation; Retinal exudate segmentation; Retinal vessels segmentation; Retina screening

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APA (6th Edition):

Almotiri, J. (2018). A Multi-Anatomical Retinal Structure Segmentation System For Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding . (Thesis). University of Bridgeport. Retrieved from https://scholarworks.bridgeport.edu/xmlui/handle/123456789/2494

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):

Almotiri, Jasem. “A Multi-Anatomical Retinal Structure Segmentation System For Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding .” 2018. Thesis, University of Bridgeport. Accessed March 01, 2021. https://scholarworks.bridgeport.edu/xmlui/handle/123456789/2494.

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

MLA Handbook (7th Edition):

Almotiri, Jasem. “A Multi-Anatomical Retinal Structure Segmentation System For Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding .” 2018. Web. 01 Mar 2021.

Vancouver:

Almotiri J. A Multi-Anatomical Retinal Structure Segmentation System For Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding . [Internet] [Thesis]. University of Bridgeport; 2018. [cited 2021 Mar 01]. Available from: https://scholarworks.bridgeport.edu/xmlui/handle/123456789/2494.

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

Council of Science Editors:

Almotiri J. A Multi-Anatomical Retinal Structure Segmentation System For Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding . [Thesis]. University of Bridgeport; 2018. Available from: https://scholarworks.bridgeport.edu/xmlui/handle/123456789/2494

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

24. Aysha, V. Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods.

Degree: 2013, Cochin University of Science and Technology

The work is intended to study the following important aspects of document image processing and develop new methods. (1) Segmentation ofdocument images using adaptive interval… (more)

Subjects/Keywords: Document Image Processing; Image Segmentation; Image Compression; Fuzzy Sets; Simulated Annealing

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

APA (6th Edition):

Aysha, V. (2013). Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods. (Thesis). Cochin University of Science and Technology. Retrieved from http://dyuthi.cusat.ac.in/purl/3679

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):

Aysha, V. “Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods.” 2013. Thesis, Cochin University of Science and Technology. Accessed March 01, 2021. http://dyuthi.cusat.ac.in/purl/3679.

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

MLA Handbook (7th Edition):

Aysha, V. “Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods.” 2013. Web. 01 Mar 2021.

Vancouver:

Aysha V. Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods. [Internet] [Thesis]. Cochin University of Science and Technology; 2013. [cited 2021 Mar 01]. Available from: http://dyuthi.cusat.ac.in/purl/3679.

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

Council of Science Editors:

Aysha V. Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods. [Thesis]. Cochin University of Science and Technology; 2013. Available from: http://dyuthi.cusat.ac.in/purl/3679

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

25. Li, Yujie. Study on Optical Image Quality Improvement for Underwater Environment : 水中環境における光学画像の画質改善に関する研究.

Degree: 博士(工学), 2017, Kyushu Institute of Technology / 九州工業大学

 Since the 1960s, autonomous underwater vehicles (AUVs) and unmanned underwater vehicles (UUVs) have been used for deep-sea exploration. Sonar sensors also have been extensively used… (more)

Subjects/Keywords: Under Imaging; Image Enhancement; Image Segmentation; Image Dehazing

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

APA (6th Edition):

Li, Y. (2017). Study on Optical Image Quality Improvement for Underwater Environment : 水中環境における光学画像の画質改善に関する研究. (Thesis). Kyushu Institute of Technology / 九州工業大学. Retrieved from http://hdl.handle.net/10228/5597

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, Yujie. “Study on Optical Image Quality Improvement for Underwater Environment : 水中環境における光学画像の画質改善に関する研究.” 2017. Thesis, Kyushu Institute of Technology / 九州工業大学. Accessed March 01, 2021. http://hdl.handle.net/10228/5597.

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

MLA Handbook (7th Edition):

Li, Yujie. “Study on Optical Image Quality Improvement for Underwater Environment : 水中環境における光学画像の画質改善に関する研究.” 2017. Web. 01 Mar 2021.

Vancouver:

Li Y. Study on Optical Image Quality Improvement for Underwater Environment : 水中環境における光学画像の画質改善に関する研究. [Internet] [Thesis]. Kyushu Institute of Technology / 九州工業大学; 2017. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/10228/5597.

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

Council of Science Editors:

Li Y. Study on Optical Image Quality Improvement for Underwater Environment : 水中環境における光学画像の画質改善に関する研究. [Thesis]. Kyushu Institute of Technology / 九州工業大学; 2017. Available from: http://hdl.handle.net/10228/5597

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


University of Melbourne

26. LIANG, XI. Breast cancer detection and diagnosis in dynamic contrast-enhanced magnetic resonance imaging.

Degree: 2013, University of Melbourne

 Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast is a medical imaging tool used to detect and diagnose breast disease. A DCE-MR image is… (more)

Subjects/Keywords: image processing; MRI; breast cancer; image registration; image segmentation

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

APA (6th Edition):

LIANG, X. (2013). Breast cancer detection and diagnosis in dynamic contrast-enhanced magnetic resonance imaging. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/52778

Chicago Manual of Style (16th Edition):

LIANG, XI. “Breast cancer detection and diagnosis in dynamic contrast-enhanced magnetic resonance imaging.” 2013. Doctoral Dissertation, University of Melbourne. Accessed March 01, 2021. http://hdl.handle.net/11343/52778.

MLA Handbook (7th Edition):

LIANG, XI. “Breast cancer detection and diagnosis in dynamic contrast-enhanced magnetic resonance imaging.” 2013. Web. 01 Mar 2021.

Vancouver:

LIANG X. Breast cancer detection and diagnosis in dynamic contrast-enhanced magnetic resonance imaging. [Internet] [Doctoral dissertation]. University of Melbourne; 2013. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/11343/52778.

Council of Science Editors:

LIANG X. Breast cancer detection and diagnosis in dynamic contrast-enhanced magnetic resonance imaging. [Doctoral Dissertation]. University of Melbourne; 2013. Available from: http://hdl.handle.net/11343/52778


University of Illinois – Urbana-Champaign

27. Xu, Ning. Image and video object selection.

Degree: PhD, Electrical & Computer Engr, 2017, University of Illinois – Urbana-Champaign

Image and video object selection present fundamental research problems in the computer vision field and have many practical applications. They are important technologies in image(more)

Subjects/Keywords: Object selection; Computer vision; Deep learning; Image segmentation; Video segmentation

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

APA (6th Edition):

Xu, N. (2017). Image and video object selection. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/99515

Chicago Manual of Style (16th Edition):

Xu, Ning. “Image and video object selection.” 2017. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed March 01, 2021. http://hdl.handle.net/2142/99515.

MLA Handbook (7th Edition):

Xu, Ning. “Image and video object selection.” 2017. Web. 01 Mar 2021.

Vancouver:

Xu N. Image and video object selection. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2017. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/2142/99515.

Council of Science Editors:

Xu N. Image and video object selection. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2017. Available from: http://hdl.handle.net/2142/99515


Ohio University

28. Wang, Zhewei. Laplacian Pyramid FCN for Robust Follicle Segmentation.

Degree: MS, Biomedical Engineering (Engineering and Technology), 2019, Ohio University

 The thyroid gland secretes hormones that regulate metabolic rate and protein synthesis. At the microscopic level, the thyroid consists of three major components: follicles, follicular… (more)

Subjects/Keywords: Biomedical Engineering; Deep Learning; Image Segmentation; Follicle Segmentation

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APA (6th Edition):

Wang, Z. (2019). Laplacian Pyramid FCN for Robust Follicle Segmentation. (Masters Thesis). Ohio University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1565620740447982

Chicago Manual of Style (16th Edition):

Wang, Zhewei. “Laplacian Pyramid FCN for Robust Follicle Segmentation.” 2019. Masters Thesis, Ohio University. Accessed March 01, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1565620740447982.

MLA Handbook (7th Edition):

Wang, Zhewei. “Laplacian Pyramid FCN for Robust Follicle Segmentation.” 2019. Web. 01 Mar 2021.

Vancouver:

Wang Z. Laplacian Pyramid FCN for Robust Follicle Segmentation. [Internet] [Masters thesis]. Ohio University; 2019. [cited 2021 Mar 01]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1565620740447982.

Council of Science Editors:

Wang Z. Laplacian Pyramid FCN for Robust Follicle Segmentation. [Masters Thesis]. Ohio University; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1565620740447982


University of Adelaide

29. He, Tong. Efficient Scene Parsing with Imagery and Point Cloud Data.

Degree: 2020, University of Adelaide

 Scene parsing, aiming to provide a comprehensive understanding of the scene, is a fundamental task in the field of computer vision and remains a challenging… (more)

Subjects/Keywords: Scene parsing; image semantic segmentation; point cloud instance segmentation

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APA (6th Edition):

He, T. (2020). Efficient Scene Parsing with Imagery and Point Cloud Data. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/129534

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):

He, Tong. “Efficient Scene Parsing with Imagery and Point Cloud Data.” 2020. Thesis, University of Adelaide. Accessed March 01, 2021. http://hdl.handle.net/2440/129534.

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

MLA Handbook (7th Edition):

He, Tong. “Efficient Scene Parsing with Imagery and Point Cloud Data.” 2020. Web. 01 Mar 2021.

Vancouver:

He T. Efficient Scene Parsing with Imagery and Point Cloud Data. [Internet] [Thesis]. University of Adelaide; 2020. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/2440/129534.

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

Council of Science Editors:

He T. Efficient Scene Parsing with Imagery and Point Cloud Data. [Thesis]. University of Adelaide; 2020. Available from: http://hdl.handle.net/2440/129534

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


University of California – Merced

30. Safar, Simon. Learning shape priors with neural networks.

Degree: Electrical Engineering and Computer Science, 2014, University of California – Merced

 We propose two methods for object segmentation by combining learned shape priors with local features. The first, Max-Margin Boltzmann Machines, learns shapes in an unsupervised… (more)

Subjects/Keywords: Computer science; image; learning; object; segmentation

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APA (6th Edition):

Safar, S. (2014). Learning shape priors with neural networks. (Thesis). University of California – Merced. Retrieved from http://www.escholarship.org/uc/item/709186x7

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):

Safar, Simon. “Learning shape priors with neural networks.” 2014. Thesis, University of California – Merced. Accessed March 01, 2021. http://www.escholarship.org/uc/item/709186x7.

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

MLA Handbook (7th Edition):

Safar, Simon. “Learning shape priors with neural networks.” 2014. Web. 01 Mar 2021.

Vancouver:

Safar S. Learning shape priors with neural networks. [Internet] [Thesis]. University of California – Merced; 2014. [cited 2021 Mar 01]. Available from: http://www.escholarship.org/uc/item/709186x7.

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

Council of Science Editors:

Safar S. Learning shape priors with neural networks. [Thesis]. University of California – Merced; 2014. Available from: http://www.escholarship.org/uc/item/709186x7

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

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