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You searched for +publisher:"Rutgers University" +contributor:("Metaxas, Dimitris N"). Showing records 1 – 17 of 17 total matches.

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Rutgers University

1. Zhong, Lin, 1985-. Single image deblurring with or without face prior and its applications.

Degree: PhD, Computer Science, 2015, Rutgers University

The motion blur is one of the most difficult challenges in photography, which is generated from the relative motion between the sensor and the scene… (more)

Subjects/Keywords: Image processing – Digital techniques; Human face recognition (Computer science)

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APA (6th Edition):

Zhong, Lin, 1. (2015). Single image deblurring with or without face prior and its applications. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/47622/

Chicago Manual of Style (16th Edition):

Zhong, Lin, 1985-. “Single image deblurring with or without face prior and its applications.” 2015. Doctoral Dissertation, Rutgers University. Accessed July 14, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/47622/.

MLA Handbook (7th Edition):

Zhong, Lin, 1985-. “Single image deblurring with or without face prior and its applications.” 2015. Web. 14 Jul 2020.

Vancouver:

Zhong, Lin 1. Single image deblurring with or without face prior and its applications. [Internet] [Doctoral dissertation]. Rutgers University; 2015. [cited 2020 Jul 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/47622/.

Council of Science Editors:

Zhong, Lin 1. Single image deblurring with or without face prior and its applications. [Doctoral Dissertation]. Rutgers University; 2015. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/47622/


Rutgers University

2. Gao, Mingchen, 1988-. Cardiac reconstruction and analysis from high resolution CT images.

Degree: PhD, Computer Science, 2014, Rutgers University

Heart disease is a major cause of mortality worldwide. Detecting/diagnosing such diseases in their early stages is critical, and heavily depends on non-invasive imaging methods,… (more)

Subjects/Keywords: Heart – Tomography; Heart – Imaging; Heart – Diseases – Diagnosis

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APA (6th Edition):

Gao, Mingchen, 1. (2014). Cardiac reconstruction and analysis from high resolution CT images. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/45272/

Chicago Manual of Style (16th Edition):

Gao, Mingchen, 1988-. “Cardiac reconstruction and analysis from high resolution CT images.” 2014. Doctoral Dissertation, Rutgers University. Accessed July 14, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/45272/.

MLA Handbook (7th Edition):

Gao, Mingchen, 1988-. “Cardiac reconstruction and analysis from high resolution CT images.” 2014. Web. 14 Jul 2020.

Vancouver:

Gao, Mingchen 1. Cardiac reconstruction and analysis from high resolution CT images. [Internet] [Doctoral dissertation]. Rutgers University; 2014. [cited 2020 Jul 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45272/.

Council of Science Editors:

Gao, Mingchen 1. Cardiac reconstruction and analysis from high resolution CT images. [Doctoral Dissertation]. Rutgers University; 2014. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45272/


Rutgers University

3. Yan, Zhennan, 1983-. Robust medical image recognition and segmentation.

Degree: PhD, Computer Science, 2016, Rutgers University

In recent decades, with increasing amount of medical data, clinical trials are designed and conducted to explore whether a medical strategy, treatment, or device is… (more)

Subjects/Keywords: Diagnostic imaging; Computer vision

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APA (6th Edition):

Yan, Zhennan, 1. (2016). Robust medical image recognition and segmentation. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/51515/

Chicago Manual of Style (16th Edition):

Yan, Zhennan, 1983-. “Robust medical image recognition and segmentation.” 2016. Doctoral Dissertation, Rutgers University. Accessed July 14, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/51515/.

MLA Handbook (7th Edition):

Yan, Zhennan, 1983-. “Robust medical image recognition and segmentation.” 2016. Web. 14 Jul 2020.

Vancouver:

Yan, Zhennan 1. Robust medical image recognition and segmentation. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2020 Jul 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51515/.

Council of Science Editors:

Yan, Zhennan 1. Robust medical image recognition and segmentation. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51515/


Rutgers University

4. 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 July 14, 2020. 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. 14 Jul 2020.

Vancouver:

Senlet, Turgay 1. Visual localization, semantic video segmentation and labeling using satellite maps. [Internet] [Doctoral dissertation]. Rutgers University; 2015. [cited 2020 Jul 14]. 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/


Rutgers University

5. Huang, Yuchi, 1979-. Hypergraph based visual categorization and segmentation.

Degree: PhD, Computer Science, 2010, Rutgers University

This dissertation explores original techniques for the construction of hypergraph models for computer vision applications. A hypergraph is a generalization of a pairwise simple graph,… (more)

Subjects/Keywords: Hypergraphs; Computer vision – Mathematical models

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APA (6th Edition):

Huang, Yuchi, 1. (2010). Hypergraph based visual categorization and segmentation. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000056373

Chicago Manual of Style (16th Edition):

Huang, Yuchi, 1979-. “Hypergraph based visual categorization and segmentation.” 2010. Doctoral Dissertation, Rutgers University. Accessed July 14, 2020. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000056373.

MLA Handbook (7th Edition):

Huang, Yuchi, 1979-. “Hypergraph based visual categorization and segmentation.” 2010. Web. 14 Jul 2020.

Vancouver:

Huang, Yuchi 1. Hypergraph based visual categorization and segmentation. [Internet] [Doctoral dissertation]. Rutgers University; 2010. [cited 2020 Jul 14]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000056373.

Council of Science Editors:

Huang, Yuchi 1. Hypergraph based visual categorization and segmentation. [Doctoral Dissertation]. Rutgers University; 2010. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000056373


Rutgers University

6. Liu, Jingjing, 1985-. Exploiting multispectral and contextual information to improve human detection.

Degree: PhD, Computer Science, 2017, Rutgers University

Human detection has various applications, e.g., autonomous driving car, surveillance system, and retail. In this dissertation, we first exploit multispectral images (i.e., RGB and thermal… (more)

Subjects/Keywords: Robotics – Human factors; Human-robot interaction

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APA (6th Edition):

Liu, Jingjing, 1. (2017). Exploiting multispectral and contextual information to improve human detection. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/55564/

Chicago Manual of Style (16th Edition):

Liu, Jingjing, 1985-. “Exploiting multispectral and contextual information to improve human detection.” 2017. Doctoral Dissertation, Rutgers University. Accessed July 14, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/55564/.

MLA Handbook (7th Edition):

Liu, Jingjing, 1985-. “Exploiting multispectral and contextual information to improve human detection.” 2017. Web. 14 Jul 2020.

Vancouver:

Liu, Jingjing 1. Exploiting multispectral and contextual information to improve human detection. [Internet] [Doctoral dissertation]. Rutgers University; 2017. [cited 2020 Jul 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55564/.

Council of Science Editors:

Liu, Jingjing 1. Exploiting multispectral and contextual information to improve human detection. [Doctoral Dissertation]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55564/


Rutgers University

7. Zhu, Yan, 1986-. Towards active and interactive visual learning.

Degree: PhD, Computer Science, 2017, Rutgers University

Modern computer vision models mostly rely on massive human annotated datasets for supervised training. The models are typically learned from the supervision of static datasets… (more)

Subjects/Keywords: Computer vision

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APA (6th Edition):

Zhu, Yan, 1. (2017). Towards active and interactive visual learning. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/55812/

Chicago Manual of Style (16th Edition):

Zhu, Yan, 1986-. “Towards active and interactive visual learning.” 2017. Doctoral Dissertation, Rutgers University. Accessed July 14, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/55812/.

MLA Handbook (7th Edition):

Zhu, Yan, 1986-. “Towards active and interactive visual learning.” 2017. Web. 14 Jul 2020.

Vancouver:

Zhu, Yan 1. Towards active and interactive visual learning. [Internet] [Doctoral dissertation]. Rutgers University; 2017. [cited 2020 Jul 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55812/.

Council of Science Editors:

Zhu, Yan 1. Towards active and interactive visual learning. [Doctoral Dissertation]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55812/


Rutgers University

8. Peng, Xi, 1986-. Learning disentangled representations in deep visual analysis.

Degree: PhD, Computer Science, 2018, Rutgers University

Learning reliable and interpretable representations is one of the fundamental challenges in machine learning and computer vision. Over the last decade, deep neural networks have… (more)

Subjects/Keywords: Machine learning

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APA (6th Edition):

Peng, Xi, 1. (2018). Learning disentangled representations in deep visual analysis. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/56078/

Chicago Manual of Style (16th Edition):

Peng, Xi, 1986-. “Learning disentangled representations in deep visual analysis.” 2018. Doctoral Dissertation, Rutgers University. Accessed July 14, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/56078/.

MLA Handbook (7th Edition):

Peng, Xi, 1986-. “Learning disentangled representations in deep visual analysis.” 2018. Web. 14 Jul 2020.

Vancouver:

Peng, Xi 1. Learning disentangled representations in deep visual analysis. [Internet] [Doctoral dissertation]. Rutgers University; 2018. [cited 2020 Jul 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/56078/.

Council of Science Editors:

Peng, Xi 1. Learning disentangled representations in deep visual analysis. [Doctoral Dissertation]. Rutgers University; 2018. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/56078/


Rutgers University

9. Liu, Bo, 1984-. Optimization in sparse learning: from convexity to non-convexity.

Degree: PhD, Computer Science, 2019, Rutgers University

 Nowadays, the explosive data scale increase provides an unprecedented opportunity to apply machine learning methods in various application domains. The high-dimension data representation proposes curse… (more)

Subjects/Keywords: Machine learning

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APA (6th Edition):

Liu, Bo, 1. (2019). Optimization in sparse learning: from convexity to non-convexity. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/60032/

Chicago Manual of Style (16th Edition):

Liu, Bo, 1984-. “Optimization in sparse learning: from convexity to non-convexity.” 2019. Doctoral Dissertation, Rutgers University. Accessed July 14, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/60032/.

MLA Handbook (7th Edition):

Liu, Bo, 1984-. “Optimization in sparse learning: from convexity to non-convexity.” 2019. Web. 14 Jul 2020.

Vancouver:

Liu, Bo 1. Optimization in sparse learning: from convexity to non-convexity. [Internet] [Doctoral dissertation]. Rutgers University; 2019. [cited 2020 Jul 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/60032/.

Council of Science Editors:

Liu, Bo 1. Optimization in sparse learning: from convexity to non-convexity. [Doctoral Dissertation]. Rutgers University; 2019. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/60032/


Rutgers University

10. Yang, Dong, 1987-. Deformable models and machine learning for large-scale cardiac MRI image analytics.

Degree: PhD, Computer Science, 2019, Rutgers University

The analysis of left ventricle (LV) wall motion is an important step for understanding cardiac functioning mechanisms, and clinical diagnosis of ventricular diseases. For example,… (more)

Subjects/Keywords: Heart  – Magnetic resonance imaging; Machine learning

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APA (6th Edition):

Yang, Dong, 1. (2019). Deformable models and machine learning for large-scale cardiac MRI image analytics. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/61044/

Chicago Manual of Style (16th Edition):

Yang, Dong, 1987-. “Deformable models and machine learning for large-scale cardiac MRI image analytics.” 2019. Doctoral Dissertation, Rutgers University. Accessed July 14, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/61044/.

MLA Handbook (7th Edition):

Yang, Dong, 1987-. “Deformable models and machine learning for large-scale cardiac MRI image analytics.” 2019. Web. 14 Jul 2020.

Vancouver:

Yang, Dong 1. Deformable models and machine learning for large-scale cardiac MRI image analytics. [Internet] [Doctoral dissertation]. Rutgers University; 2019. [cited 2020 Jul 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/61044/.

Council of Science Editors:

Yang, Dong 1. Deformable models and machine learning for large-scale cardiac MRI image analytics. [Doctoral Dissertation]. Rutgers University; 2019. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/61044/


Rutgers University

11. Tan, Chaowei, 1983-. Machine learning based image segmentation for large-scale osteoarthritis analysis.

Degree: PhD, Computer Science, 2020, Rutgers University

Osteoarthritis (OA) is the most common degenerative joint disease worldwide, tending to occur in the joints of hip and knee. Large adult population in the… (more)

Subjects/Keywords: Osteoarthritis analysis; Osteoarthritis  – Imaging

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APA (6th Edition):

Tan, Chaowei, 1. (2020). Machine learning based image segmentation for large-scale osteoarthritis analysis. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/62751/

Chicago Manual of Style (16th Edition):

Tan, Chaowei, 1983-. “Machine learning based image segmentation for large-scale osteoarthritis analysis.” 2020. Doctoral Dissertation, Rutgers University. Accessed July 14, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/62751/.

MLA Handbook (7th Edition):

Tan, Chaowei, 1983-. “Machine learning based image segmentation for large-scale osteoarthritis analysis.” 2020. Web. 14 Jul 2020.

Vancouver:

Tan, Chaowei 1. Machine learning based image segmentation for large-scale osteoarthritis analysis. [Internet] [Doctoral dissertation]. Rutgers University; 2020. [cited 2020 Jul 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/62751/.

Council of Science Editors:

Tan, Chaowei 1. Machine learning based image segmentation for large-scale osteoarthritis analysis. [Doctoral Dissertation]. Rutgers University; 2020. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/62751/

12. Trivedi, Chintan, 1993-. Camera based detection of the onset of cognitive fatigue.

Degree: MS, Computer Science, 2017, Rutgers University

 The onset of cognitive fatigue is associated with a period of transient, subconscious decrease in maximal cognitive ability, typically influencing decision making. The ability to… (more)

Subjects/Keywords: Machine learning; Mental fatigue

…sent over to Rutgers University for the purpose of this research work. 2.1.2 Experiment… 

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APA (6th Edition):

Trivedi, Chintan, 1. (2017). Camera based detection of the onset of cognitive fatigue. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/54034/

Chicago Manual of Style (16th Edition):

Trivedi, Chintan, 1993-. “Camera based detection of the onset of cognitive fatigue.” 2017. Masters Thesis, Rutgers University. Accessed July 14, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/54034/.

MLA Handbook (7th Edition):

Trivedi, Chintan, 1993-. “Camera based detection of the onset of cognitive fatigue.” 2017. Web. 14 Jul 2020.

Vancouver:

Trivedi, Chintan 1. Camera based detection of the onset of cognitive fatigue. [Internet] [Masters thesis]. Rutgers University; 2017. [cited 2020 Jul 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/54034/.

Council of Science Editors:

Trivedi, Chintan 1. Camera based detection of the onset of cognitive fatigue. [Masters Thesis]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/54034/

13. Michael, Nicholas. A face tracking system for dynamic event recognition: application to continuous recognition of non-manual markers of American sign language and to deception detection by kinesic analysis.

Degree: Computer Science, 2012, Rutgers University

Subjects/Keywords: Face perception; Human-computer interaction; American Sign Language; Facial expression – Testing

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APA (6th Edition):

Michael, N. (2012). A face tracking system for dynamic event recognition: application to continuous recognition of non-manual markers of American sign language and to deception detection by kinesic analysis. (Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000064148

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):

Michael, Nicholas. “A face tracking system for dynamic event recognition: application to continuous recognition of non-manual markers of American sign language and to deception detection by kinesic analysis.” 2012. Thesis, Rutgers University. Accessed July 14, 2020. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000064148.

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

MLA Handbook (7th Edition):

Michael, Nicholas. “A face tracking system for dynamic event recognition: application to continuous recognition of non-manual markers of American sign language and to deception detection by kinesic analysis.” 2012. Web. 14 Jul 2020.

Vancouver:

Michael N. A face tracking system for dynamic event recognition: application to continuous recognition of non-manual markers of American sign language and to deception detection by kinesic analysis. [Internet] [Thesis]. Rutgers University; 2012. [cited 2020 Jul 14]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000064148.

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

Council of Science Editors:

Michael N. A face tracking system for dynamic event recognition: application to continuous recognition of non-manual markers of American sign language and to deception detection by kinesic analysis. [Thesis]. Rutgers University; 2012. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000064148

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

14. Cui, Xinyi, 1983-. Towards accurate group activity analysis in videos: robust saliency detection and effective feature modeling.

Degree: Computer Science, 2013, Rutgers University

Subjects/Keywords: Computer vision – Research; Human activity recognition – Research; Video surveillance

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APA (6th Edition):

Cui, Xinyi, 1. (2013). Towards accurate group activity analysis in videos: robust saliency detection and effective feature modeling. (Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068833

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):

Cui, Xinyi, 1983-. “Towards accurate group activity analysis in videos: robust saliency detection and effective feature modeling.” 2013. Thesis, Rutgers University. Accessed July 14, 2020. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068833.

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

MLA Handbook (7th Edition):

Cui, Xinyi, 1983-. “Towards accurate group activity analysis in videos: robust saliency detection and effective feature modeling.” 2013. Web. 14 Jul 2020.

Vancouver:

Cui, Xinyi 1. Towards accurate group activity analysis in videos: robust saliency detection and effective feature modeling. [Internet] [Thesis]. Rutgers University; 2013. [cited 2020 Jul 14]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068833.

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

Council of Science Editors:

Cui, Xinyi 1. Towards accurate group activity analysis in videos: robust saliency detection and effective feature modeling. [Thesis]. Rutgers University; 2013. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068833

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

15. Zhang, Shaoting, 1982-. Towards robust and effective shape prior modeling: sparse shape composition.

Degree: Computer Science, 2012, Rutgers University

Subjects/Keywords: Shapes; Computer simulation; Shapes – Computer simulation

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APA (6th Edition):

Zhang, Shaoting, 1. (2012). Towards robust and effective shape prior modeling: sparse shape composition. (Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000064198

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, Shaoting, 1982-. “Towards robust and effective shape prior modeling: sparse shape composition.” 2012. Thesis, Rutgers University. Accessed July 14, 2020. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000064198.

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

MLA Handbook (7th Edition):

Zhang, Shaoting, 1982-. “Towards robust and effective shape prior modeling: sparse shape composition.” 2012. Web. 14 Jul 2020.

Vancouver:

Zhang, Shaoting 1. Towards robust and effective shape prior modeling: sparse shape composition. [Internet] [Thesis]. Rutgers University; 2012. [cited 2020 Jul 14]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000064198.

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

Council of Science Editors:

Zhang, Shaoting 1. Towards robust and effective shape prior modeling: sparse shape composition. [Thesis]. Rutgers University; 2012. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000064198

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

16. Pasternack, Robert M, 1985-. Developing a time-dynamic, label-free assay for apoptosis based on optical Gabor filtering.

Degree: PhD, Biomedical Engineering, 2011, Rutgers University

Apoptosis is a fundamental process in the homeostasis and development of mammals, dysfunction of its regulation is implicated in human disease, and it is of… (more)

Subjects/Keywords: Apoptosis; Optoelectronic devices

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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APA (6th Edition):

Pasternack, Robert M, 1. (2011). Developing a time-dynamic, label-free assay for apoptosis based on optical Gabor filtering. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061437

Chicago Manual of Style (16th Edition):

Pasternack, Robert M, 1985-. “Developing a time-dynamic, label-free assay for apoptosis based on optical Gabor filtering.” 2011. Doctoral Dissertation, Rutgers University. Accessed July 14, 2020. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061437.

MLA Handbook (7th Edition):

Pasternack, Robert M, 1985-. “Developing a time-dynamic, label-free assay for apoptosis based on optical Gabor filtering.” 2011. Web. 14 Jul 2020.

Vancouver:

Pasternack, Robert M 1. Developing a time-dynamic, label-free assay for apoptosis based on optical Gabor filtering. [Internet] [Doctoral dissertation]. Rutgers University; 2011. [cited 2020 Jul 14]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061437.

Council of Science Editors:

Pasternack, Robert M 1. Developing a time-dynamic, label-free assay for apoptosis based on optical Gabor filtering. [Doctoral Dissertation]. Rutgers University; 2011. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061437

17. Dalal, Chintan, 1981-. High-dimensional manifold geostatistics.

Degree: PhD, Computer Science, 2019, Rutgers University

An understanding of the Earth's climate system benefits all sectors of the economy and environment. Several challenges faced when modeling the Earth's climate system include:… (more)

Subjects/Keywords: Geology  – Statistical methods

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APA (6th Edition):

Dalal, Chintan, 1. (2019). High-dimensional manifold geostatistics. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/60136/

Chicago Manual of Style (16th Edition):

Dalal, Chintan, 1981-. “High-dimensional manifold geostatistics.” 2019. Doctoral Dissertation, Rutgers University. Accessed July 14, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/60136/.

MLA Handbook (7th Edition):

Dalal, Chintan, 1981-. “High-dimensional manifold geostatistics.” 2019. Web. 14 Jul 2020.

Vancouver:

Dalal, Chintan 1. High-dimensional manifold geostatistics. [Internet] [Doctoral dissertation]. Rutgers University; 2019. [cited 2020 Jul 14]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/60136/.

Council of Science Editors:

Dalal, Chintan 1. High-dimensional manifold geostatistics. [Doctoral Dissertation]. Rutgers University; 2019. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/60136/

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