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You searched for +publisher:"Rutgers University" +contributor:("Kulikowski, Casimir"). Showing records 1 – 20 of 20 total matches.

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Rutgers University

1. Dilsizian, Mark. Hybrid discriminative-generative methods for human pose reconstruction from monocular imagery.

Degree: PhD, Computer Science, 2016, Rutgers University

Estimating 3D human pose from monocular images is an important and challenging problem in computer vision with numerous applications including human-computer interaction, human activity recognition,… (more)

Subjects/Keywords: Computer vision

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APA (6th Edition):

Dilsizian, M. (2016). Hybrid discriminative-generative methods for human pose reconstruction from monocular imagery. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/49953/

Chicago Manual of Style (16th Edition):

Dilsizian, Mark. “Hybrid discriminative-generative methods for human pose reconstruction from monocular imagery.” 2016. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/49953/.

MLA Handbook (7th Edition):

Dilsizian, Mark. “Hybrid discriminative-generative methods for human pose reconstruction from monocular imagery.” 2016. Web. 19 Oct 2019.

Vancouver:

Dilsizian M. Hybrid discriminative-generative methods for human pose reconstruction from monocular imagery. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2019 Oct 19]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/49953/.

Council of Science Editors:

Dilsizian M. Hybrid discriminative-generative methods for human pose reconstruction from monocular imagery. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/49953/


Rutgers University

2. Gang, Joshua E., 1992-. Color composition.

Degree: MS, Computer Science, 2016, Rutgers University

 Recent research has used crowd sourced corpora of language to learn grounded meanings that associate color descriptions with uncertain regions in hue-saturation-value color space. In… (more)

Subjects/Keywords: Color

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APA (6th Edition):

Gang, Joshua E., 1. (2016). Color composition. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/49965/

Chicago Manual of Style (16th Edition):

Gang, Joshua E., 1992-. “Color composition.” 2016. Masters Thesis, Rutgers University. Accessed October 19, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/49965/.

MLA Handbook (7th Edition):

Gang, Joshua E., 1992-. “Color composition.” 2016. Web. 19 Oct 2019.

Vancouver:

Gang, Joshua E. 1. Color composition. [Internet] [Masters thesis]. Rutgers University; 2016. [cited 2019 Oct 19]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/49965/.

Council of Science Editors:

Gang, Joshua E. 1. Color composition. [Masters Thesis]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/49965/


Rutgers University

3. Toso, Rodrigo Franco, 1981-. Adaptive clustering with a variance-aware criterion: an alternative to k-means.

Degree: PhD, Computer Science, 2016, Rutgers University

This research investigates the effectiveness of a non-convex clustering criterion with the ability to discriminate clusters by means of quadratic boundaries that take into account… (more)

Subjects/Keywords: Cluster analysis

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APA (6th Edition):

Toso, Rodrigo Franco, 1. (2016). Adaptive clustering with a variance-aware criterion: an alternative to k-means. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/50234/

Chicago Manual of Style (16th Edition):

Toso, Rodrigo Franco, 1981-. “Adaptive clustering with a variance-aware criterion: an alternative to k-means.” 2016. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/50234/.

MLA Handbook (7th Edition):

Toso, Rodrigo Franco, 1981-. “Adaptive clustering with a variance-aware criterion: an alternative to k-means.” 2016. Web. 19 Oct 2019.

Vancouver:

Toso, Rodrigo Franco 1. Adaptive clustering with a variance-aware criterion: an alternative to k-means. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2019 Oct 19]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/50234/.

Council of Science Editors:

Toso, Rodrigo Franco 1. Adaptive clustering with a variance-aware criterion: an alternative to k-means. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/50234/


Rutgers University

4. Bakry, Amr M., 1981-. Leveraging image manifolds for visual learning.

Degree: PhD, Computer Science, 2016, Rutgers University

The field of computer vision has recently witnessed remarkable progress, due mainly to visual data availability and machine learning advances. Modeling the visual data is… (more)

Subjects/Keywords: Computer vision; Visual learning

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APA (6th Edition):

Bakry, Amr M., 1. (2016). Leveraging image manifolds for visual learning. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/51184/

Chicago Manual of Style (16th Edition):

Bakry, Amr M., 1981-. “Leveraging image manifolds for visual learning.” 2016. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/51184/.

MLA Handbook (7th Edition):

Bakry, Amr M., 1981-. “Leveraging image manifolds for visual learning.” 2016. Web. 19 Oct 2019.

Vancouver:

Bakry, Amr M. 1. Leveraging image manifolds for visual learning. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2019 Oct 19]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51184/.

Council of Science Editors:

Bakry, Amr M. 1. Leveraging image manifolds for visual learning. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51184/


Rutgers University

5. Elhoseiny, Mohamed. Language guided visual perception.

Degree: PhD, Computer Science, 2016, Rutgers University

People typically learn through exposure to visual facts associated with linguistic descriptions. For instance, teaching visual concepts to children is often accompanied by descriptions in… (more)

Subjects/Keywords: Computer vision; Visual Perception

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APA (6th Edition):

Elhoseiny, M. (2016). Language guided visual perception. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/51280/

Chicago Manual of Style (16th Edition):

Elhoseiny, Mohamed. “Language guided visual perception.” 2016. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/51280/.

MLA Handbook (7th Edition):

Elhoseiny, Mohamed. “Language guided visual perception.” 2016. Web. 19 Oct 2019.

Vancouver:

Elhoseiny M. Language guided visual perception. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2019 Oct 19]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51280/.

Council of Science Editors:

Elhoseiny M. Language guided visual perception. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51280/


Rutgers University

6. Khan, Faisal M., 1981-. Semi-supervised transductive regression for survival analysis in medical prognostics.

Degree: PhD, Computer Science, 2016, Rutgers University

The central challenge in predictive modeling for survival analysis in medical prognostics is the management of censored observations in the data. While time-to-event predictions can… (more)

Subjects/Keywords: Survival analysis (Biometry)

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APA (6th Edition):

Khan, Faisal M., 1. (2016). Semi-supervised transductive regression for survival analysis in medical prognostics. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/51331/

Chicago Manual of Style (16th Edition):

Khan, Faisal M., 1981-. “Semi-supervised transductive regression for survival analysis in medical prognostics.” 2016. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/51331/.

MLA Handbook (7th Edition):

Khan, Faisal M., 1981-. “Semi-supervised transductive regression for survival analysis in medical prognostics.” 2016. Web. 19 Oct 2019.

Vancouver:

Khan, Faisal M. 1. Semi-supervised transductive regression for survival analysis in medical prognostics. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2019 Oct 19]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51331/.

Council of Science Editors:

Khan, Faisal M. 1. Semi-supervised transductive regression for survival analysis in medical prognostics. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51331/


Rutgers University

7. Ye, Jiankuan, 1976-. Experimental study and geometrical analysis of a linear programming support vector machine.

Degree: PhD, Computer Science, 2011, Rutgers University

This dissertation describes a systematic study of a linear programming SVM proposed by Vapnik, which directly minimizes the ratio of support vectors to the number… (more)

Subjects/Keywords: Linear programming – Data processing; Support vector machines; Quadratic programming – Computer programs; Machine learning

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APA (6th Edition):

Ye, Jiankuan, 1. (2011). Experimental study and geometrical analysis of a linear programming support vector machine. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057715

Chicago Manual of Style (16th Edition):

Ye, Jiankuan, 1976-. “Experimental study and geometrical analysis of a linear programming support vector machine.” 2011. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057715.

MLA Handbook (7th Edition):

Ye, Jiankuan, 1976-. “Experimental study and geometrical analysis of a linear programming support vector machine.” 2011. Web. 19 Oct 2019.

Vancouver:

Ye, Jiankuan 1. Experimental study and geometrical analysis of a linear programming support vector machine. [Internet] [Doctoral dissertation]. Rutgers University; 2011. [cited 2019 Oct 19]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057715.

Council of Science Editors:

Ye, Jiankuan 1. Experimental study and geometrical analysis of a linear programming support vector machine. [Doctoral Dissertation]. Rutgers University; 2011. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057715


Rutgers University

8. Yang, Xiang, 1987-. Robust method in photogrammetric reconstruction of geometric primitives in solid modeling.

Degree: PhD, Mechanical and Aerospace Engineering, 2017, Rutgers University

The 3D point cloud is a widely used data format obtained from scanning a 3D model, either by using active 3D laser range scanners or… (more)

Subjects/Keywords: Robust statistics

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APA (6th Edition):

Yang, Xiang, 1. (2017). Robust method in photogrammetric reconstruction of geometric primitives in solid modeling. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/55777/

Chicago Manual of Style (16th Edition):

Yang, Xiang, 1987-. “Robust method in photogrammetric reconstruction of geometric primitives in solid modeling.” 2017. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/55777/.

MLA Handbook (7th Edition):

Yang, Xiang, 1987-. “Robust method in photogrammetric reconstruction of geometric primitives in solid modeling.” 2017. Web. 19 Oct 2019.

Vancouver:

Yang, Xiang 1. Robust method in photogrammetric reconstruction of geometric primitives in solid modeling. [Internet] [Doctoral dissertation]. Rutgers University; 2017. [cited 2019 Oct 19]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55777/.

Council of Science Editors:

Yang, Xiang 1. Robust method in photogrammetric reconstruction of geometric primitives in solid modeling. [Doctoral Dissertation]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55777/

9. Arora, Ravneet Singh, 1985-. Towards automated classification of fine-art painting style: a comparative study.

Degree: MS, Computer Science, 2012, Rutgers University

 This thesis presents a comparative study of different classification methodologies for the task of fine-art genre classification. The problem of painting classification involves classifying new… (more)

Subjects/Keywords: Painting – Classification; Computer vision; Pattern recognition systems

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APA (6th Edition):

Arora, Ravneet Singh, 1. (2012). Towards automated classification of fine-art painting style: a comparative study. (Masters Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000066603

Chicago Manual of Style (16th Edition):

Arora, Ravneet Singh, 1985-. “Towards automated classification of fine-art painting style: a comparative study.” 2012. Masters Thesis, Rutgers University. Accessed October 19, 2019. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000066603.

MLA Handbook (7th Edition):

Arora, Ravneet Singh, 1985-. “Towards automated classification of fine-art painting style: a comparative study.” 2012. Web. 19 Oct 2019.

Vancouver:

Arora, Ravneet Singh 1. Towards automated classification of fine-art painting style: a comparative study. [Internet] [Masters thesis]. Rutgers University; 2012. [cited 2019 Oct 19]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000066603.

Council of Science Editors:

Arora, Ravneet Singh 1. Towards automated classification of fine-art painting style: a comparative study. [Masters Thesis]. Rutgers University; 2012. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000066603

10. Nouri, Ali, 1980-. Efficient model-based exploration in continuous state-space environments.

Degree: PhD, Computer Science, 2011, Rutgers University

The impetus for exploration in reinforcement learning (RL) is decreasing uncertainty about the environment for the purpose of better decision making. As such, exploration plays… (more)

Subjects/Keywords: Decision making; Reinforcement learning – Methodology; Machine learning

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APA (6th Edition):

Nouri, Ali, 1. (2011). Efficient model-based exploration in continuous state-space environments. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057652

Chicago Manual of Style (16th Edition):

Nouri, Ali, 1980-. “Efficient model-based exploration in continuous state-space environments.” 2011. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057652.

MLA Handbook (7th Edition):

Nouri, Ali, 1980-. “Efficient model-based exploration in continuous state-space environments.” 2011. Web. 19 Oct 2019.

Vancouver:

Nouri, Ali 1. Efficient model-based exploration in continuous state-space environments. [Internet] [Doctoral dissertation]. Rutgers University; 2011. [cited 2019 Oct 19]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057652.

Council of Science Editors:

Nouri, Ali 1. Efficient model-based exploration in continuous state-space environments. [Doctoral Dissertation]. Rutgers University; 2011. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057652

11. Torki, Marwan, 1982-. Learning the manifolds of local features and their spatial arrangements.

Degree: Computer Science, 2011, Rutgers University

Subjects/Keywords: Computer vision

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APA (6th Edition):

Torki, Marwan, 1. (2011). Learning the manifolds of local features and their spatial arrangements. (Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063668

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):

Torki, Marwan, 1982-. “Learning the manifolds of local features and their spatial arrangements.” 2011. Thesis, Rutgers University. Accessed October 19, 2019. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063668.

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

MLA Handbook (7th Edition):

Torki, Marwan, 1982-. “Learning the manifolds of local features and their spatial arrangements.” 2011. Web. 19 Oct 2019.

Vancouver:

Torki, Marwan 1. Learning the manifolds of local features and their spatial arrangements. [Internet] [Thesis]. Rutgers University; 2011. [cited 2019 Oct 19]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063668.

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

Council of Science Editors:

Torki, Marwan 1. Learning the manifolds of local features and their spatial arrangements. [Thesis]. Rutgers University; 2011. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063668

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

12. Zhao, Zhipeng, 1973-. Towards a local-global visual feature-based framework for recognition:.

Degree: PhD, Computer Science, 2009, Rutgers University

General object and activity recognition is a fundamental problem in computer vision that has been the subject of much research. Traditional approaches include model based… (more)

Subjects/Keywords: Computer vision

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APA (6th Edition):

Zhao, Zhipeng, 1. (2009). Towards a local-global visual feature-based framework for recognition:. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051935

Chicago Manual of Style (16th Edition):

Zhao, Zhipeng, 1973-. “Towards a local-global visual feature-based framework for recognition:.” 2009. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051935.

MLA Handbook (7th Edition):

Zhao, Zhipeng, 1973-. “Towards a local-global visual feature-based framework for recognition:.” 2009. Web. 19 Oct 2019.

Vancouver:

Zhao, Zhipeng 1. Towards a local-global visual feature-based framework for recognition:. [Internet] [Doctoral dissertation]. Rutgers University; 2009. [cited 2019 Oct 19]. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051935.

Council of Science Editors:

Zhao, Zhipeng 1. Towards a local-global visual feature-based framework for recognition:. [Doctoral Dissertation]. Rutgers University; 2009. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051935

13. Liu, Baiyang, 1983-. Selection-based dictionary learning for sparse representation in visual tracking.

Degree: Computer Science, 2012, Rutgers University

Subjects/Keywords: Computer vision

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APA (6th Edition):

Liu, Baiyang, 1. (2012). Selection-based dictionary learning for sparse representation in visual tracking. (Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000066893

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

Chicago Manual of Style (16th Edition):

Liu, Baiyang, 1983-. “Selection-based dictionary learning for sparse representation in visual tracking.” 2012. Thesis, Rutgers University. Accessed October 19, 2019. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000066893.

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

MLA Handbook (7th Edition):

Liu, Baiyang, 1983-. “Selection-based dictionary learning for sparse representation in visual tracking.” 2012. Web. 19 Oct 2019.

Vancouver:

Liu, Baiyang 1. Selection-based dictionary learning for sparse representation in visual tracking. [Internet] [Thesis]. Rutgers University; 2012. [cited 2019 Oct 19]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000066893.

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

Council of Science Editors:

Liu, Baiyang 1. Selection-based dictionary learning for sparse representation in visual tracking. [Thesis]. Rutgers University; 2012. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000066893

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


Rutgers University

14. Balakrishnan, Suhrid. Classifiers of massive and structured data problems: algorithms and applications.

Degree: PhD, Computer Science, 2007, Rutgers University

The last two decades have seen the emergence of vast and unprecedented data repositories. Extraordinary opportunities now present themselves for new data analysis methods that… (more)

Subjects/Keywords: Data mining; Machine learning; Artificial intelligence

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APA (6th Edition):

Balakrishnan, S. (2007). Classifiers of massive and structured data problems: algorithms and applications. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.15772

Chicago Manual of Style (16th Edition):

Balakrishnan, Suhrid. “Classifiers of massive and structured data problems: algorithms and applications.” 2007. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.15772.

MLA Handbook (7th Edition):

Balakrishnan, Suhrid. “Classifiers of massive and structured data problems: algorithms and applications.” 2007. Web. 19 Oct 2019.

Vancouver:

Balakrishnan S. Classifiers of massive and structured data problems: algorithms and applications. [Internet] [Doctoral dissertation]. Rutgers University; 2007. [cited 2019 Oct 19]. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.15772.

Council of Science Editors:

Balakrishnan S. Classifiers of massive and structured data problems: algorithms and applications. [Doctoral Dissertation]. Rutgers University; 2007. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.15772


Rutgers University

15. Huang, Yang, 1976-. Computational approaches to identifying molecular associations in high-throughput biological data.

Degree: PhD, Computer Science, 2007, Rutgers University

Biomolecules, such as proteins and nucleic acids, are the building blocks of living organisms. Their complex interactions and associations are the key to understanding the… (more)

Subjects/Keywords: Bioinformatics; Computational biology

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APA (6th Edition):

Huang, Yang, 1. (2007). Computational approaches to identifying molecular associations in high-throughput biological data. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16094

Chicago Manual of Style (16th Edition):

Huang, Yang, 1976-. “Computational approaches to identifying molecular associations in high-throughput biological data.” 2007. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16094.

MLA Handbook (7th Edition):

Huang, Yang, 1976-. “Computational approaches to identifying molecular associations in high-throughput biological data.” 2007. Web. 19 Oct 2019.

Vancouver:

Huang, Yang 1. Computational approaches to identifying molecular associations in high-throughput biological data. [Internet] [Doctoral dissertation]. Rutgers University; 2007. [cited 2019 Oct 19]. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16094.

Council of Science Editors:

Huang, Yang 1. Computational approaches to identifying molecular associations in high-throughput biological data. [Doctoral Dissertation]. Rutgers University; 2007. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16094


Rutgers University

16. Huang, Pai-Hsi. Protein homology detection with sparse models.

Degree: PhD, Computer Science, 2008, Rutgers University

Establishing structural or functional relationship between sequences, for instance to infer the structural class of an unannotated protein, is a key task in biological analysis.… (more)

Subjects/Keywords: Proteins – Analysis – Mathematical models; Homology theory

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APA (6th Edition):

Huang, P. (2008). Protein homology detection with sparse models. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17493

Chicago Manual of Style (16th Edition):

Huang, Pai-Hsi. “Protein homology detection with sparse models.” 2008. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17493.

MLA Handbook (7th Edition):

Huang, Pai-Hsi. “Protein homology detection with sparse models.” 2008. Web. 19 Oct 2019.

Vancouver:

Huang P. Protein homology detection with sparse models. [Internet] [Doctoral dissertation]. Rutgers University; 2008. [cited 2019 Oct 19]. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17493.

Council of Science Editors:

Huang P. Protein homology detection with sparse models. [Doctoral Dissertation]. Rutgers University; 2008. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17493


Rutgers University

17. Tuzel, Cuneyt Oncel. Learning on Riemannian manifolds for interpretation of visual environments.

Degree: Computer Science, 2008, Rutgers University

Subjects/Keywords: Computer vision; Riemannian manifolds

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APA (6th Edition):

Tuzel, C. O. (2008). Learning on Riemannian manifolds for interpretation of visual environments. (Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000050463

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):

Tuzel, Cuneyt Oncel. “Learning on Riemannian manifolds for interpretation of visual environments.” 2008. Thesis, Rutgers University. Accessed October 19, 2019. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000050463.

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

MLA Handbook (7th Edition):

Tuzel, Cuneyt Oncel. “Learning on Riemannian manifolds for interpretation of visual environments.” 2008. Web. 19 Oct 2019.

Vancouver:

Tuzel CO. Learning on Riemannian manifolds for interpretation of visual environments. [Internet] [Thesis]. Rutgers University; 2008. [cited 2019 Oct 19]. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000050463.

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

Council of Science Editors:

Tuzel CO. Learning on Riemannian manifolds for interpretation of visual environments. [Thesis]. Rutgers University; 2008. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000050463

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


Rutgers University

18. Lytkin, Nikita I. Variance-based clustering methods and higher order data transformations and their applications:.

Degree: PhD, Computer Science, 2009, Rutgers University

Two approaches have been proposed in statistical and machine learning communities in order to address the problem of uncovering clusters with complex structure. One approach… (more)

Subjects/Keywords: Multivariate analysis; Cluster analysis

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

APA (6th Edition):

Lytkin, N. I. (2009). Variance-based clustering methods and higher order data transformations and their applications:. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051869

Chicago Manual of Style (16th Edition):

Lytkin, Nikita I. “Variance-based clustering methods and higher order data transformations and their applications:.” 2009. Doctoral Dissertation, Rutgers University. Accessed October 19, 2019. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051869.

MLA Handbook (7th Edition):

Lytkin, Nikita I. “Variance-based clustering methods and higher order data transformations and their applications:.” 2009. Web. 19 Oct 2019.

Vancouver:

Lytkin NI. Variance-based clustering methods and higher order data transformations and their applications:. [Internet] [Doctoral dissertation]. Rutgers University; 2009. [cited 2019 Oct 19]. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051869.

Council of Science Editors:

Lytkin NI. Variance-based clustering methods and higher order data transformations and their applications:. [Doctoral Dissertation]. Rutgers University; 2009. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051869


Rutgers University

19. Le, Thang Viet, 1970-. Clustering by graph density variation analysis (GDVA) with density-based cluster validity indices (DVI).

Degree: Computer Science, 2011, Rutgers University

Subjects/Keywords: Cluster analysis—Computer programs

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

APA (6th Edition):

Le, Thang Viet, 1. (2011). Clustering by graph density variation analysis (GDVA) with density-based cluster validity indices (DVI). (Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063506

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):

Le, Thang Viet, 1970-. “Clustering by graph density variation analysis (GDVA) with density-based cluster validity indices (DVI).” 2011. Thesis, Rutgers University. Accessed October 19, 2019. http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063506.

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

MLA Handbook (7th Edition):

Le, Thang Viet, 1970-. “Clustering by graph density variation analysis (GDVA) with density-based cluster validity indices (DVI).” 2011. Web. 19 Oct 2019.

Vancouver:

Le, Thang Viet 1. Clustering by graph density variation analysis (GDVA) with density-based cluster validity indices (DVI). [Internet] [Thesis]. Rutgers University; 2011. [cited 2019 Oct 19]. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063506.

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

Council of Science Editors:

Le, Thang Viet 1. Clustering by graph density variation analysis (GDVA) with density-based cluster validity indices (DVI). [Thesis]. Rutgers University; 2011. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063506

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


Rutgers University

20. Chakraborty, Ishani, 1982-. Object category recognition through visual-semantic context networks.

Degree: Computer Science, 2014, Rutgers University

Subjects/Keywords: Computer vision; Pattern recognition systems

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

APA (6th Edition):

Chakraborty, Ishani, 1. (2014). Object category recognition through visual-semantic context networks. (Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/42371/

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):

Chakraborty, Ishani, 1982-. “Object category recognition through visual-semantic context networks.” 2014. Thesis, Rutgers University. Accessed October 19, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/42371/.

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

MLA Handbook (7th Edition):

Chakraborty, Ishani, 1982-. “Object category recognition through visual-semantic context networks.” 2014. Web. 19 Oct 2019.

Vancouver:

Chakraborty, Ishani 1. Object category recognition through visual-semantic context networks. [Internet] [Thesis]. Rutgers University; 2014. [cited 2019 Oct 19]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/42371/.

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

Council of Science Editors:

Chakraborty, Ishani 1. Object category recognition through visual-semantic context networks. [Thesis]. Rutgers University; 2014. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/42371/

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

.