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You searched for +publisher:"University of Florida" +contributor:("Chen, Yunmei"). Showing records 1 – 24 of 24 total matches.

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University of Florida

1. Pokharel, Rosha. Robust Kernel Adaptive Learning for Online Supervised Systems.

Degree: PhD, Electrical and Computer Engineering, 2014, University of Florida

 Kernel methods are popular for their unique ability to solve non-linear problems linearly by the implicit mapping of data into high dimension feature space. They… (more)

Subjects/Keywords: Adaptive filters; Datasets; Error rates; Learning; Learning rate; Machine learning; Online learning; Signal processing; Signals; Time series; adaptive  – classification  – correntropy  – filtering  – kernel  – mixture-kernel  – multi-kernel  – online  – rkhs

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APA (6th Edition):

Pokharel, R. (2014). Robust Kernel Adaptive Learning for Online Supervised Systems. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046621

Chicago Manual of Style (16th Edition):

Pokharel, Rosha. “Robust Kernel Adaptive Learning for Online Supervised Systems.” 2014. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0046621.

MLA Handbook (7th Edition):

Pokharel, Rosha. “Robust Kernel Adaptive Learning for Online Supervised Systems.” 2014. Web. 16 Sep 2019.

Vancouver:

Pokharel R. Robust Kernel Adaptive Learning for Online Supervised Systems. [Internet] [Doctoral dissertation]. University of Florida; 2014. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0046621.

Council of Science Editors:

Pokharel R. Robust Kernel Adaptive Learning for Online Supervised Systems. [Doctoral Dissertation]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0046621


University of Florida

2. Chalasani, Rakesh. A Hierarchical Dynamic Model for Object Recognition.

Degree: PhD, Electrical and Computer Engineering, 2013, University of Florida

 This work focuses on building a hierarchical dynamic model for object recognition in video. It is inspired from predictive coding framework that is used to… (more)

Subjects/Keywords: Architectural models; Contextual information; Datasets; Dynamic modeling; Inference; Machine learning; Modeling; Multilevel models; Object recognition; Signals; cortex  – deep  – hierarchy  – learning  – recognition

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APA (6th Edition):

Chalasani, R. (2013). A Hierarchical Dynamic Model for Object Recognition. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046204

Chicago Manual of Style (16th Edition):

Chalasani, Rakesh. “A Hierarchical Dynamic Model for Object Recognition.” 2013. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0046204.

MLA Handbook (7th Edition):

Chalasani, Rakesh. “A Hierarchical Dynamic Model for Object Recognition.” 2013. Web. 16 Sep 2019.

Vancouver:

Chalasani R. A Hierarchical Dynamic Model for Object Recognition. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0046204.

Council of Science Editors:

Chalasani R. A Hierarchical Dynamic Model for Object Recognition. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0046204


University of Florida

3. Feng, Wei. Charge Transport Analysis for Lightning.

Degree: PhD, Mathematics, 2013, University of Florida

 Charge rearrangement is analyzed for an intracloud flash on August 24th 2007. The analysis employed data from a balloon borne electric field sensor, or Esonde,… (more)

Subjects/Keywords: Altitude; Charge density; Electric current; Electric fields; Geometric planes; Ionospheric currents; Lightning; Sprites; Storms; Thunderstorms; charge-transport  – electric-field  – lightning  – sprite

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APA (6th Edition):

Feng, W. (2013). Charge Transport Analysis for Lightning. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046174

Chicago Manual of Style (16th Edition):

Feng, Wei. “Charge Transport Analysis for Lightning.” 2013. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0046174.

MLA Handbook (7th Edition):

Feng, Wei. “Charge Transport Analysis for Lightning.” 2013. Web. 16 Sep 2019.

Vancouver:

Feng W. Charge Transport Analysis for Lightning. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0046174.

Council of Science Editors:

Feng W. Charge Transport Analysis for Lightning. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0046174


University of Florida

4. Chen, Fuhua. Multiphase Image Segmentation Based on Intensity Statistics Modeling and Applications.

Degree: PhD, Mathematics, 2012, University of Florida

 Image segmentation is  the first stage of image processing and analysis. The result of image segmentation is used for image post-processing. In computer vision, segmentation… (more)

Subjects/Keywords: Algorithms; Approximation; Computer vision; Gaussian distributions; Gray matter; Image processing; Membership functions; Pixels; Stochastic models; White matter; image  – multiphase  – processing  – segmentation  – supervised

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APA (6th Edition):

Chen, F. (2012). Multiphase Image Segmentation Based on Intensity Statistics Modeling and Applications. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044393

Chicago Manual of Style (16th Edition):

Chen, Fuhua. “Multiphase Image Segmentation Based on Intensity Statistics Modeling and Applications.” 2012. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0044393.

MLA Handbook (7th Edition):

Chen, Fuhua. “Multiphase Image Segmentation Based on Intensity Statistics Modeling and Applications.” 2012. Web. 16 Sep 2019.

Vancouver:

Chen F. Multiphase Image Segmentation Based on Intensity Statistics Modeling and Applications. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0044393.

Council of Science Editors:

Chen F. Multiphase Image Segmentation Based on Intensity Statistics Modeling and Applications. [Doctoral Dissertation]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044393


University of Florida

5. Phan, Dung. Topics in Global Optimization Ellipsoidal Bisection, Graph Partitioning and Sparse Reconstruction.

Degree: PhD, Mathematics, 2010, University of Florida

 In this dissertation, we develop theories and practical algorithms for optimization problems which arise from science, economics and engineering. First, an ellipsoidal branch and bound… (more)

Subjects/Keywords: Algorithms; Approximation; Ellipsoids; Function values; Integers; Linear programming; Mathematics; Objective functions; Quadratic programming; Underestimates; bound, branch, convex, global, graph, image, nonmonotone, nonsmooth, optimization, partitioning, quadratic, reconstruction, sparse, sublinear, underestimation

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APA (6th Edition):

Phan, D. (2010). Topics in Global Optimization Ellipsoidal Bisection, Graph Partitioning and Sparse Reconstruction. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0041470

Chicago Manual of Style (16th Edition):

Phan, Dung. “Topics in Global Optimization Ellipsoidal Bisection, Graph Partitioning and Sparse Reconstruction.” 2010. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0041470.

MLA Handbook (7th Edition):

Phan, Dung. “Topics in Global Optimization Ellipsoidal Bisection, Graph Partitioning and Sparse Reconstruction.” 2010. Web. 16 Sep 2019.

Vancouver:

Phan D. Topics in Global Optimization Ellipsoidal Bisection, Graph Partitioning and Sparse Reconstruction. [Internet] [Doctoral dissertation]. University of Florida; 2010. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0041470.

Council of Science Editors:

Phan D. Topics in Global Optimization Ellipsoidal Bisection, Graph Partitioning and Sparse Reconstruction. [Doctoral Dissertation]. University of Florida; 2010. Available from: http://ufdc.ufl.edu/UFE0041470


University of Florida

6. Liu, Meng. Modeling and Algorithms for Compressive Magnetic Resonance (MR) Image Reconstruction.

Degree: PhD, Mathematics, 2014, University of Florida

This thesis is devoted to mathematical modelings and numerical algorithms developing for solving image reconstruction problems arising from single- or multi-contrast compressive magnetic resonance (MR) imaging. Advisors/Committee Members: CHEN,YUNMEI (committee chair), ZHANG,LEI (committee member), JURY,MICHAEL THOMAS (committee member), WU,SAMUEL SHANGWU (committee member).

Subjects/Keywords: Image contrast; Image reconstruction; Images of transformations; Imaging; Magnetic resonance; Magnetic resonance imaging; Maps; Mathematical robustness; Maximum likelihood estimations; Payment protection insurance; algorithms  – imaging  – modeling  – multi-contrast  – optimization  – reconstruction

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APA (6th Edition):

Liu, M. (2014). Modeling and Algorithms for Compressive Magnetic Resonance (MR) Image Reconstruction. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0047481

Chicago Manual of Style (16th Edition):

Liu, Meng. “Modeling and Algorithms for Compressive Magnetic Resonance (MR) Image Reconstruction.” 2014. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0047481.

MLA Handbook (7th Edition):

Liu, Meng. “Modeling and Algorithms for Compressive Magnetic Resonance (MR) Image Reconstruction.” 2014. Web. 16 Sep 2019.

Vancouver:

Liu M. Modeling and Algorithms for Compressive Magnetic Resonance (MR) Image Reconstruction. [Internet] [Doctoral dissertation]. University of Florida; 2014. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0047481.

Council of Science Editors:

Liu M. Modeling and Algorithms for Compressive Magnetic Resonance (MR) Image Reconstruction. [Doctoral Dissertation]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0047481


University of Florida

7. Lee, Soyoung. Quantitative Image Quality Assessment and Qualitiy Assurance of Advanced Imaging Systems for Igrt.

Degree: PhD, Biomedical Engineering, 2015, University of Florida

 With the advent of advanced treatment techniques, imaging guidance plays crucial roles in the image-guided radiation therapy (IGRT). Two imaging modalities - electronic portal imaging… (more)

Subjects/Keywords: Amplitude; Breathing; Calibration; Dosage; Image analysis; Image reconstruction; Imaging; Pixels; Signals; Tumors; 4dcbct  – igrt  – image-quality  – tumore-motion-reconstruction

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APA (6th Edition):

Lee, S. (2015). Quantitative Image Quality Assessment and Qualitiy Assurance of Advanced Imaging Systems for Igrt. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0049273

Chicago Manual of Style (16th Edition):

Lee, Soyoung. “Quantitative Image Quality Assessment and Qualitiy Assurance of Advanced Imaging Systems for Igrt.” 2015. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0049273.

MLA Handbook (7th Edition):

Lee, Soyoung. “Quantitative Image Quality Assessment and Qualitiy Assurance of Advanced Imaging Systems for Igrt.” 2015. Web. 16 Sep 2019.

Vancouver:

Lee S. Quantitative Image Quality Assessment and Qualitiy Assurance of Advanced Imaging Systems for Igrt. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0049273.

Council of Science Editors:

Lee S. Quantitative Image Quality Assessment and Qualitiy Assurance of Advanced Imaging Systems for Igrt. [Doctoral Dissertation]. University of Florida; 2015. Available from: http://ufdc.ufl.edu/UFE0049273


University of Florida

8. Posirca, Iulia M. Variational Models for Simultaneous Image Segmentation and Noise Removal.

Degree: PhD, Mathematics, 2012, University of Florida

 We present two projects for simultaneous image segmentation and noise removal. The first project concerns the images corrupted with Gaussian noise and the second one… (more)

Subjects/Keywords: Data smoothing; Image processing; Image reconstruction; Imaging; Mathematics; Modeling; Pixels; Statistical models; Supernova remnants; Ultrasonography; image  – noise  – segmentation  – variational

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APA (6th Edition):

Posirca, I. M. (2012). Variational Models for Simultaneous Image Segmentation and Noise Removal. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044953

Chicago Manual of Style (16th Edition):

Posirca, Iulia M. “Variational Models for Simultaneous Image Segmentation and Noise Removal.” 2012. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0044953.

MLA Handbook (7th Edition):

Posirca, Iulia M. “Variational Models for Simultaneous Image Segmentation and Noise Removal.” 2012. Web. 16 Sep 2019.

Vancouver:

Posirca IM. Variational Models for Simultaneous Image Segmentation and Noise Removal. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0044953.

Council of Science Editors:

Posirca IM. Variational Models for Simultaneous Image Segmentation and Noise Removal. [Doctoral Dissertation]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044953


University of Florida

9. Zhao, Songlin. From Fixed to Adaptive Budget Robust Kernel Adaptive Filtering.

Degree: PhD, Electrical and Computer Engineering, 2012, University of Florida

 Recently, owning to universal modeling capacity, convexity in performance surface and modest computational complexity, kernel adaptive filters have attracted more and more attention. Even though… (more)

Subjects/Keywords: Adaptive filters; Approximation; Computational complexity; Cost functions; Input data; Neural networks; Pruning; Signal processing; Simulations; Time series; kenrel  – songlin

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APA (6th Edition):

Zhao, S. (2012). From Fixed to Adaptive Budget Robust Kernel Adaptive Filtering. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044951

Chicago Manual of Style (16th Edition):

Zhao, Songlin. “From Fixed to Adaptive Budget Robust Kernel Adaptive Filtering.” 2012. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0044951.

MLA Handbook (7th Edition):

Zhao, Songlin. “From Fixed to Adaptive Budget Robust Kernel Adaptive Filtering.” 2012. Web. 16 Sep 2019.

Vancouver:

Zhao S. From Fixed to Adaptive Budget Robust Kernel Adaptive Filtering. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0044951.

Council of Science Editors:

Zhao S. From Fixed to Adaptive Budget Robust Kernel Adaptive Filtering. [Doctoral Dissertation]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044951


University of Florida

10. Lee, Jin-Seop. Image registration by using statistical information.

Degree: PhD, Mathematics, 2013, University of Florida

 Image registration has been an important subject in many areas including remote sensing, computer vision, and medical imaging. It has been intensively studied and many… (more)

Subjects/Keywords: Computerized axial tomography; Coordinate transformations; Correlation coefficients; Diagnostic imaging; Image processing; Images; Images of transformations; Lungs; Parametric models; Statistical models; aos  – image  – information  – measure

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APA (6th Edition):

Lee, J. (2013). Image registration by using statistical information. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045405

Chicago Manual of Style (16th Edition):

Lee, Jin-Seop. “Image registration by using statistical information.” 2013. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0045405.

MLA Handbook (7th Edition):

Lee, Jin-Seop. “Image registration by using statistical information.” 2013. Web. 16 Sep 2019.

Vancouver:

Lee J. Image registration by using statistical information. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0045405.

Council of Science Editors:

Lee J. Image registration by using statistical information. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045405


University of Florida

11. Prosper, Olivia Felicia. Modeling Heterogeneities in Malaria.

Degree: PhD, Mathematics, 2012, University of Florida

 Malaria is an extremely complex disease that continues to thwart the efforts to control it in many countries around the globe. This dissertation presents three… (more)

Subjects/Keywords: Disease models; Diseases; Human movement; Infections; Malaria; Mathematical models; Modeling; Parametric models; Parasites; Vaccinations; biology  – competition  – control  – differential  – epidemiology  – equations  – estimation  – falciparum  – invasion  – malaria  – mathematical  – metapopulation  – model  – multi  – number  – optimal  – ordinary  – parameter  – reproduction  – species  – vaccination  – vivax

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APA (6th Edition):

Prosper, O. F. (2012). Modeling Heterogeneities in Malaria. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044010

Chicago Manual of Style (16th Edition):

Prosper, Olivia Felicia. “Modeling Heterogeneities in Malaria.” 2012. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0044010.

MLA Handbook (7th Edition):

Prosper, Olivia Felicia. “Modeling Heterogeneities in Malaria.” 2012. Web. 16 Sep 2019.

Vancouver:

Prosper OF. Modeling Heterogeneities in Malaria. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0044010.

Council of Science Editors:

Prosper OF. Modeling Heterogeneities in Malaria. [Doctoral Dissertation]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044010


University of Florida

12. Yashtini, Maryam. Fast TV-Regularized Large-Scale and Ill-Conditioned Linear Inversion with Application to Partially Parallel Imaging.

Degree: PhD, Mathematics, 2014, University of Florida

 This research focuses on development and analysis of fast algorithms for image reconstruction problems that arise from an emerging magnetic resonance medical imaging technique known… (more)

Subjects/Keywords: Algorithms; Ergodic theory; Error rates; Image reconstruction; Imaging; Infinity; Inverse problems; Magnetic resonance imaging; Objective functions; Payment protection insurance; algorithms  – convergence  – ill-condition  – mri  – optimization  – regularization

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APA (6th Edition):

Yashtini, M. (2014). Fast TV-Regularized Large-Scale and Ill-Conditioned Linear Inversion with Application to Partially Parallel Imaging. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0047095

Chicago Manual of Style (16th Edition):

Yashtini, Maryam. “Fast TV-Regularized Large-Scale and Ill-Conditioned Linear Inversion with Application to Partially Parallel Imaging.” 2014. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0047095.

MLA Handbook (7th Edition):

Yashtini, Maryam. “Fast TV-Regularized Large-Scale and Ill-Conditioned Linear Inversion with Application to Partially Parallel Imaging.” 2014. Web. 16 Sep 2019.

Vancouver:

Yashtini M. Fast TV-Regularized Large-Scale and Ill-Conditioned Linear Inversion with Application to Partially Parallel Imaging. [Internet] [Doctoral dissertation]. University of Florida; 2014. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0047095.

Council of Science Editors:

Yashtini M. Fast TV-Regularized Large-Scale and Ill-Conditioned Linear Inversion with Application to Partially Parallel Imaging. [Doctoral Dissertation]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0047095


University of Florida

13. Shi, Jiangli. Statistical Dependence Measure Based Multi-Model Image Registration and Registration Assisted Non-Parametric Image Segmentation.

Degree: PhD, Mathematics, 2013, University of Florida

 A series of mathematical models for image registrations are investigated in this work to provide a variety of techniques especially for medical image alignment. Analysis… (more)

Subjects/Keywords: Coordinate transformations; Cross correlation; Entropy; Image processing; Images of transformations; Linear transformations; Parametric models; Random variables; Sine function; Statistical models; dependence  – image  – measure  – registration  – segmentation  – statistical

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APA (6th Edition):

Shi, J. (2013). Statistical Dependence Measure Based Multi-Model Image Registration and Registration Assisted Non-Parametric Image Segmentation. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045845

Chicago Manual of Style (16th Edition):

Shi, Jiangli. “Statistical Dependence Measure Based Multi-Model Image Registration and Registration Assisted Non-Parametric Image Segmentation.” 2013. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0045845.

MLA Handbook (7th Edition):

Shi, Jiangli. “Statistical Dependence Measure Based Multi-Model Image Registration and Registration Assisted Non-Parametric Image Segmentation.” 2013. Web. 16 Sep 2019.

Vancouver:

Shi J. Statistical Dependence Measure Based Multi-Model Image Registration and Registration Assisted Non-Parametric Image Segmentation. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0045845.

Council of Science Editors:

Shi J. Statistical Dependence Measure Based Multi-Model Image Registration and Registration Assisted Non-Parametric Image Segmentation. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045845


University of Florida

14. Ouyang, Yuyuan. Optimal First Order Methods for a Class of Non-Smooth Convex Optimization with Applications to Image Analysis.

Degree: PhD, Mathematics, 2013, University of Florida

 This PhD Dissertation concerns optimal first order methods in convex optimization, and their applications in imaging science. The research is motivated by the rapid advances… (more)

Subjects/Keywords: Algorithms; Approximation; Data smoothing; Image reconstruction; Imaging; Payment protection insurance; Perceptron convergence procedure; Saddle points; Signals; Spherical harmonics; imaging  – nonsmooth  – optimization  – smooth  – stochastic

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APA (6th Edition):

Ouyang, Y. (2013). Optimal First Order Methods for a Class of Non-Smooth Convex Optimization with Applications to Image Analysis. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045919

Chicago Manual of Style (16th Edition):

Ouyang, Yuyuan. “Optimal First Order Methods for a Class of Non-Smooth Convex Optimization with Applications to Image Analysis.” 2013. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0045919.

MLA Handbook (7th Edition):

Ouyang, Yuyuan. “Optimal First Order Methods for a Class of Non-Smooth Convex Optimization with Applications to Image Analysis.” 2013. Web. 16 Sep 2019.

Vancouver:

Ouyang Y. Optimal First Order Methods for a Class of Non-Smooth Convex Optimization with Applications to Image Analysis. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0045919.

Council of Science Editors:

Ouyang Y. Optimal First Order Methods for a Class of Non-Smooth Convex Optimization with Applications to Image Analysis. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045919


University of Florida

15. Guo, Ying. Energy Estimates and Harnack Type Inequalities for Prescribing Curvature Type Equations with Boundary Conditions.

Degree: PhD, Mathematics, 2013, University of Florida

 For a class of semi-linear elliptic equations with critical Sobolev exponents and boundary conditions, we prove pointwise estimates for blowup solutions and energy estimates. A… (more)

Subjects/Keywords: Curvature; Distance functions; Greens function; Local maximum; Logical proofs; Mathematical inequalities; Mathematics; Maximum principle; Point estimators; Scalars; blowup  – energy  – estimate  – harnack  – inequality  – semilinear  – yamabe

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APA (6th Edition):

Guo, Y. (2013). Energy Estimates and Harnack Type Inequalities for Prescribing Curvature Type Equations with Boundary Conditions. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046218

Chicago Manual of Style (16th Edition):

Guo, Ying. “Energy Estimates and Harnack Type Inequalities for Prescribing Curvature Type Equations with Boundary Conditions.” 2013. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0046218.

MLA Handbook (7th Edition):

Guo, Ying. “Energy Estimates and Harnack Type Inequalities for Prescribing Curvature Type Equations with Boundary Conditions.” 2013. Web. 16 Sep 2019.

Vancouver:

Guo Y. Energy Estimates and Harnack Type Inequalities for Prescribing Curvature Type Equations with Boundary Conditions. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0046218.

Council of Science Editors:

Guo Y. Energy Estimates and Harnack Type Inequalities for Prescribing Curvature Type Equations with Boundary Conditions. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0046218


University of Florida

16. Zhang, Haili. Mathematical Modeling for Image Segmentation and Restoration.

Degree: PhD, Mathematics, 2013, University of Florida

 This thesis is devoted to the formulation, implementation, and improvement of mathematical models and efficient algorithms for image segmentation and image restoration using tools based… (more)

Subjects/Keywords: Algorithms; Eigenfunctions; Gray matter; Histograms; Image processing; Images of transformations; Inhomogeneity; Noise intensity; Parametric models; Pixels; algorithm  – deblurring  – denoising  – nonparametric  – restoration  – segmentation

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APA (6th Edition):

Zhang, H. (2013). Mathematical Modeling for Image Segmentation and Restoration. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045847

Chicago Manual of Style (16th Edition):

Zhang, Haili. “Mathematical Modeling for Image Segmentation and Restoration.” 2013. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0045847.

MLA Handbook (7th Edition):

Zhang, Haili. “Mathematical Modeling for Image Segmentation and Restoration.” 2013. Web. 16 Sep 2019.

Vancouver:

Zhang H. Mathematical Modeling for Image Segmentation and Restoration. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0045847.

Council of Science Editors:

Zhang H. Mathematical Modeling for Image Segmentation and Restoration. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045847


University of Florida

17. Guo, Meixi. Empirical Bayes and Likelihood Based Methods for Measurement Error Models.

Degree: PhD, Statistics, 2012, University of Florida

 Measurement error is a problem that is commonly present in data collected from human respondents. Its early appearance dates back to nearly a century ago… (more)

Subjects/Keywords: Consistent estimators; Estimators; Estimators for the mean; Linear regression; Maximum likelihood estimations; Regression analysis; Simulations; Statism; Statistical estimation; Statistical models; empirical-bayes  – james-stein-estimation  – measurement-error  – profile-likelihood  – small-area-estimation

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

APA (6th Edition):

Guo, M. (2012). Empirical Bayes and Likelihood Based Methods for Measurement Error Models. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044479

Chicago Manual of Style (16th Edition):

Guo, Meixi. “Empirical Bayes and Likelihood Based Methods for Measurement Error Models.” 2012. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0044479.

MLA Handbook (7th Edition):

Guo, Meixi. “Empirical Bayes and Likelihood Based Methods for Measurement Error Models.” 2012. Web. 16 Sep 2019.

Vancouver:

Guo M. Empirical Bayes and Likelihood Based Methods for Measurement Error Models. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0044479.

Council of Science Editors:

Guo M. Empirical Bayes and Likelihood Based Methods for Measurement Error Models. [Doctoral Dissertation]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044479


University of Florida

18. Li, Jie. Multiset Graph Partitioning.

Degree: PhD, Mathematics, 2014, University of Florida

 A continuous quadratic programming formulation is given for min-cut graphpartitioning problems. In these problems, we divide the vertices of a graph into acollection of disjoint… (more)

Subjects/Keywords: Algorithms; Integers; Mathematics; Matrices; Multisets; Necessary conditions for optimality; Polyhedrons; Quadratic programming; Separators; Vertices; bipartite  – min-cut  – optimization  – partition  – polyhedron  – programming  – projection

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APA (6th Edition):

Li, J. (2014). Multiset Graph Partitioning. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046510

Chicago Manual of Style (16th Edition):

Li, Jie. “Multiset Graph Partitioning.” 2014. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0046510.

MLA Handbook (7th Edition):

Li, Jie. “Multiset Graph Partitioning.” 2014. Web. 16 Sep 2019.

Vancouver:

Li J. Multiset Graph Partitioning. [Internet] [Doctoral dissertation]. University of Florida; 2014. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0046510.

Council of Science Editors:

Li J. Multiset Graph Partitioning. [Doctoral Dissertation]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0046510

19. Thomas, Neil B, Jr. Effect of Metallicity on Giant Planet and Brown Dwarf Formation.

Degree: PhD, Astronomy, 2015, University of Florida

 The primary goal of this work is to leverage the SDSS III Multi-object Apache Point Observatory Radial Velocity Exoplanet Large-area Survey (MARVELS) to clarify several… (more)

Subjects/Keywords: Astronomical magnitude; Calibration; Fringe; Photons; Pipelines; Pixels; Planets; Stellar spectra; Velocity; Wavelengths; exoplanet  – marvels  – metallicity

…227 14 Abstract of Dissertation Presented to the Graduate School of the University of… …Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy EFFECT… 

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APA (6th Edition):

Thomas, Neil B, J. (2015). Effect of Metallicity on Giant Planet and Brown Dwarf Formation. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0049246

Chicago Manual of Style (16th Edition):

Thomas, Neil B, Jr. “Effect of Metallicity on Giant Planet and Brown Dwarf Formation.” 2015. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0049246.

MLA Handbook (7th Edition):

Thomas, Neil B, Jr. “Effect of Metallicity on Giant Planet and Brown Dwarf Formation.” 2015. Web. 16 Sep 2019.

Vancouver:

Thomas, Neil B J. Effect of Metallicity on Giant Planet and Brown Dwarf Formation. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0049246.

Council of Science Editors:

Thomas, Neil B J. Effect of Metallicity on Giant Planet and Brown Dwarf Formation. [Doctoral Dissertation]. University of Florida; 2015. Available from: http://ufdc.ufl.edu/UFE0049246


University of Florida

20. YE,XIAOJING. Mathematical Models and Fast Numerical Algorithms in Medical Image Analysis.

Degree: PhD, Mathematics, 2011, University of Florida

A series of projects are presented to provide advanced mathematical models and numerical Advisors/Committee Members: Chen, Yunmei (committee chair), Rao, Murali (committee member), McCullough, Scott (committee member), Gopalakrishnan, Jay (committee member), Li, Jonathan (committee member).

Subjects/Keywords: Datasets; Fourier transformations; Image reconstruction; Images of transformations; Imaging; Magnetic resonance imaging; Mathematical robustness; Objective functions; Parametric models; Payment protection insurance; CONSISTENT  – CONVERGENCE  – MRI  – OPTIMIZATION  – RECONSTRUCTION  – REGISRATION  – STATISTICS

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APA (6th Edition):

YE,XIAOJING. (2011). Mathematical Models and Fast Numerical Algorithms in Medical Image Analysis. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0042919

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

YE,XIAOJING. “Mathematical Models and Fast Numerical Algorithms in Medical Image Analysis.” 2011. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0042919.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

YE,XIAOJING. “Mathematical Models and Fast Numerical Algorithms in Medical Image Analysis.” 2011. Web. 16 Sep 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

YE,XIAOJING. Mathematical Models and Fast Numerical Algorithms in Medical Image Analysis. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0042919.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

YE,XIAOJING. Mathematical Models and Fast Numerical Algorithms in Medical Image Analysis. [Doctoral Dissertation]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0042919

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Florida

21. Chen, Pengwen. Bregman Metrics and Their Applications.

Degree: PhD, Mathematics, 2007, University of Florida

 In this work, I provide three different but related discussions on a famous distance: Kullback-Leibler(KL) divergence. First, I construct two classes of distances similar to… (more)

Subjects/Keywords: Algorithms; Bending; Cost efficiency; Cost functions; Distance functions; Mathematical vectors; Minimization of cost; Optimal solutions; Triangle inequalities; Uniqueness; bregman, capacity, cardiac, classification, clustering, curve, dynamic, hellinger, kullback, metric, primal, triangle

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APA (6th Edition):

Chen, P. (2007). Bregman Metrics and Their Applications. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0021037

Chicago Manual of Style (16th Edition):

Chen, Pengwen. “Bregman Metrics and Their Applications.” 2007. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0021037.

MLA Handbook (7th Edition):

Chen, Pengwen. “Bregman Metrics and Their Applications.” 2007. Web. 16 Sep 2019.

Vancouver:

Chen P. Bregman Metrics and Their Applications. [Internet] [Doctoral dissertation]. University of Florida; 2007. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0021037.

Council of Science Editors:

Chen P. Bregman Metrics and Their Applications. [Doctoral Dissertation]. University of Florida; 2007. Available from: http://ufdc.ufl.edu/UFE0021037


University of Florida

22. Hou, Hongyan. Convergence Analysis of Orthogonal Collocation Methods for Unconstrained Optimal Control.

Degree: PhD, Mathematics, 2013, University of Florida

Subjects/Keywords: Approximation; Control theory; Degrees of polynomials; Gaussian quadratures; Interpolation; Matrices; Optimal control; Polynomials; Quadratic programming; Textual collocation; convergence; gaussian-collocation-mehtod; lebesgue-constant

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

APA (6th Edition):

Hou, H. (2013). Convergence Analysis of Orthogonal Collocation Methods for Unconstrained Optimal Control. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045697

Chicago Manual of Style (16th Edition):

Hou, Hongyan. “Convergence Analysis of Orthogonal Collocation Methods for Unconstrained Optimal Control.” 2013. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0045697.

MLA Handbook (7th Edition):

Hou, Hongyan. “Convergence Analysis of Orthogonal Collocation Methods for Unconstrained Optimal Control.” 2013. Web. 16 Sep 2019.

Vancouver:

Hou H. Convergence Analysis of Orthogonal Collocation Methods for Unconstrained Optimal Control. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0045697.

Council of Science Editors:

Hou H. Convergence Analysis of Orthogonal Collocation Methods for Unconstrained Optimal Control. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045697


University of Florida

23. Zhang, Wei. Accelerated Bundle Level Type Methods for Large Scale Convex Optimization.

Degree: PhD, Mathematics, 2017, University of Florida

Subjects/Keywords: accelerated-algorithm; bundle-level-method; convex-optimization

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APA (6th Edition):

Zhang, W. (2017). Accelerated Bundle Level Type Methods for Large Scale Convex Optimization. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0051299

Chicago Manual of Style (16th Edition):

Zhang, Wei. “Accelerated Bundle Level Type Methods for Large Scale Convex Optimization.” 2017. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0051299.

MLA Handbook (7th Edition):

Zhang, Wei. “Accelerated Bundle Level Type Methods for Large Scale Convex Optimization.” 2017. Web. 16 Sep 2019.

Vancouver:

Zhang W. Accelerated Bundle Level Type Methods for Large Scale Convex Optimization. [Internet] [Doctoral dissertation]. University of Florida; 2017. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0051299.

Council of Science Editors:

Zhang W. Accelerated Bundle Level Type Methods for Large Scale Convex Optimization. [Doctoral Dissertation]. University of Florida; 2017. Available from: http://ufdc.ufl.edu/UFE0051299


University of Florida

24. Zeng, Qingguo. Diffusion Weighted Magnetic Resonance Image Analysis and Medical Image Registration.

Degree: PhD, Mathematics, 2008, University of Florida

Subjects/Keywords: Anisotropy; Data smoothing; Experimental results; Image analysis; Image processing; Imaging; Magnetic fields; Statistical discrepancies; Tensors; White matter; adc, consistent, deformable, hardwi, image, mri, registration

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

APA (6th Edition):

Zeng, Q. (2008). Diffusion Weighted Magnetic Resonance Image Analysis and Medical Image Registration. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0021948

Chicago Manual of Style (16th Edition):

Zeng, Qingguo. “Diffusion Weighted Magnetic Resonance Image Analysis and Medical Image Registration.” 2008. Doctoral Dissertation, University of Florida. Accessed September 16, 2019. http://ufdc.ufl.edu/UFE0021948.

MLA Handbook (7th Edition):

Zeng, Qingguo. “Diffusion Weighted Magnetic Resonance Image Analysis and Medical Image Registration.” 2008. Web. 16 Sep 2019.

Vancouver:

Zeng Q. Diffusion Weighted Magnetic Resonance Image Analysis and Medical Image Registration. [Internet] [Doctoral dissertation]. University of Florida; 2008. [cited 2019 Sep 16]. Available from: http://ufdc.ufl.edu/UFE0021948.

Council of Science Editors:

Zeng Q. Diffusion Weighted Magnetic Resonance Image Analysis and Medical Image Registration. [Doctoral Dissertation]. University of Florida; 2008. Available from: http://ufdc.ufl.edu/UFE0021948

.