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University of Florida

1. Bodla, Navaneeth Kumar. Representing a Stack of Images as a Single Surface.

Degree: MS, Computer Engineering - Computer and Information Science and Engineering, 2014, University of Florida

URL: http://ufdc.ufl.edu/UFE0046844

► In this thesis we investigate a way of treating individual images and stack of images as a surface. Irrespective of what type of an image…
(more)

Subjects/Keywords: Dimensionality reduction; Entropy; Geometric angles; Geometry; Histograms; Image rotation; Images; Pixels; Principal components analysis; Surface areas; area – image – surface – vision – visualization

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

APA (6^{th} Edition):

Bodla, N. K. (2014). Representing a Stack of Images as a Single Surface. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046844

Chicago Manual of Style (16^{th} Edition):

Bodla, Navaneeth Kumar. “Representing a Stack of Images as a Single Surface.” 2014. Masters Thesis, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0046844.

MLA Handbook (7^{th} Edition):

Bodla, Navaneeth Kumar. “Representing a Stack of Images as a Single Surface.” 2014. Web. 22 Oct 2019.

Vancouver:

Bodla NK. Representing a Stack of Images as a Single Surface. [Internet] [Masters thesis]. University of Florida; 2014. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0046844.

Council of Science Editors:

Bodla NK. Representing a Stack of Images as a Single Surface. [Masters Thesis]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0046844

University of Florida

2. Chandran,Manu. Analysis of Bayesian Group-Lasso in Regression Models.

Degree: MS, Electrical and Computer Engineering, 2011, University of Florida

URL: http://ufdc.ufl.edu/UFE0043490

► The Group-Lasso estimator, used in regression analysis, does not calculate the variance estimates of regression coefficients. Such estimates are important, since they represent the confidence…
(more)

Subjects/Keywords: Datasets; Error rates; Group size; Group structure; Linear regression; Machine learning; Mathematical variables; Parametric models; Regression analysis; Statistical discrepancies; bayesian – feature – group – lasso – selection

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APA (6^{th} Edition):

Chandran,Manu. (2011). Analysis of Bayesian Group-Lasso in Regression Models. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043490

Note: this citation may be lacking information needed for this citation format:

Author name may be incomplete

Chicago Manual of Style (16^{th} Edition):

Chandran,Manu. “Analysis of Bayesian Group-Lasso in Regression Models.” 2011. Masters Thesis, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0043490.

Note: this citation may be lacking information needed for this citation format:

Author name may be incomplete

MLA Handbook (7^{th} Edition):

Chandran,Manu. “Analysis of Bayesian Group-Lasso in Regression Models.” 2011. Web. 22 Oct 2019.

Note: this citation may be lacking information needed for this citation format:

Author name may be incomplete

Vancouver:

Chandran,Manu. Analysis of Bayesian Group-Lasso in Regression Models. [Internet] [Masters thesis]. University of Florida; 2011. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0043490.

Author name may be incomplete

Council of Science Editors:

Chandran,Manu. Analysis of Bayesian Group-Lasso in Regression Models. [Masters Thesis]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043490

Author name may be incomplete

University of Florida

3. P George, Clint. A Realm-based Question Answering System using Probabilistic Modeling.

Degree: MS, Computer Engineering - Computer and Information Science and Engineering, 2010, University of Florida

URL: http://ufdc.ufl.edu/UFE0042585

► Conventional search engines traditionally perform key-word based searches of web documents. Since the wealth of information from the web is huge and often represented in…
(more)

Subjects/Keywords: Cosine function; Domain ontologies; Engines; Model trains; Ontology; Regression analysis; Tires; Web pages; Whales; Wikipedia; lda, lerning, qa, ranking, topics

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APA (6^{th} Edition):

P George, C. (2010). A Realm-based Question Answering System using Probabilistic Modeling. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0042585

Chicago Manual of Style (16^{th} Edition):

P George, Clint. “A Realm-based Question Answering System using Probabilistic Modeling.” 2010. Masters Thesis, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0042585.

MLA Handbook (7^{th} Edition):

P George, Clint. “A Realm-based Question Answering System using Probabilistic Modeling.” 2010. Web. 22 Oct 2019.

Vancouver:

P George C. A Realm-based Question Answering System using Probabilistic Modeling. [Internet] [Masters thesis]. University of Florida; 2010. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0042585.

Council of Science Editors:

P George C. A Realm-based Question Answering System using Probabilistic Modeling. [Masters Thesis]. University of Florida; 2010. Available from: http://ufdc.ufl.edu/UFE0042585

University of Florida

4. Posadas, Brianna B. Development of Detection Algorithms for Apple Disease Using Hyperspectral Data.

Degree: MS, Agricultural and Biological Engineering, 2016, University of Florida

URL: http://ufdc.ufl.edu/UFE0049996

► Fuji apples are one of the top selling exports for South Korea bringing in over $233.4 million in 2013. However, during the last few decades,…
(more)

Subjects/Keywords: Apples; Dimensionality reduction; Diseases; Fungicides; Orchards; Pixels; Principal components analysis; Reflectance; Spices; Wavelengths; apples – classifier – hyperspectral – imagery – korea – reflectance

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APA (6^{th} Edition):

Posadas, B. B. (2016). Development of Detection Algorithms for Apple Disease Using Hyperspectral Data. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0049996

Chicago Manual of Style (16^{th} Edition):

Posadas, Brianna B. “Development of Detection Algorithms for Apple Disease Using Hyperspectral Data.” 2016. Masters Thesis, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0049996.

MLA Handbook (7^{th} Edition):

Posadas, Brianna B. “Development of Detection Algorithms for Apple Disease Using Hyperspectral Data.” 2016. Web. 22 Oct 2019.

Vancouver:

Posadas BB. Development of Detection Algorithms for Apple Disease Using Hyperspectral Data. [Internet] [Masters thesis]. University of Florida; 2016. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0049996.

Council of Science Editors:

Posadas BB. Development of Detection Algorithms for Apple Disease Using Hyperspectral Data. [Masters Thesis]. University of Florida; 2016. Available from: http://ufdc.ufl.edu/UFE0049996

University of Florida

5. BAGRECHA,PRIYANK D. Correntropy for Shape-Based Matching and Retrieval of Objects in Color Images.

Degree: MS, Electrical and Computer Engineering, 2011, University of Florida

URL: http://ufdc.ufl.edu/UFE0042296

► The majority of shape matching algorithms use either shape landmarks or features extracted from the shape boundary. Automatic extraction of these landmarks or features from…
(more)

Subjects/Keywords: Crabs; Databases; Density estimation; Entropy; Geometric shapes; Image databases; Image retrieval; Information retrieval; Snakes; Surface contours; ACTIVECONTOUR – CORRENTROPY – IMAGERETRIEVAL – NONPARAMETRIC – SHAPEMATCHING

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APA (6^{th} Edition):

D, B. (2011). Correntropy for Shape-Based Matching and Retrieval of Objects in Color Images. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0042296

Chicago Manual of Style (16^{th} Edition):

D, BAGRECHA,PRIYANK. “Correntropy for Shape-Based Matching and Retrieval of Objects in Color Images.” 2011. Masters Thesis, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0042296.

MLA Handbook (7^{th} Edition):

D, BAGRECHA,PRIYANK. “Correntropy for Shape-Based Matching and Retrieval of Objects in Color Images.” 2011. Web. 22 Oct 2019.

Vancouver:

D B. Correntropy for Shape-Based Matching and Retrieval of Objects in Color Images. [Internet] [Masters thesis]. University of Florida; 2011. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0042296.

Council of Science Editors:

D B. Correntropy for Shape-Based Matching and Retrieval of Objects in Color Images. [Masters Thesis]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0042296

University of Florida

6. Dranishnikov, Dmitri Alexander. Bayesian Hyperspectral Unmixing with Multivariate Beta Distributions.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2014, University of Florida

URL: http://ufdc.ufl.edu/UFE0046690

► Many existing geometrical and statistical methods for endmember detection and spectral unmixing for Hyperspectral Image (HSI) data focus on the Linear Mixing Model (LMM). However,…
(more)

Subjects/Keywords: Covariance; Datasets; Estimation methods; Markov chains; Modeling; Parametric models; Pixels; Proportions; Sample size; Statistical discrepancies; bayesian – beta – copula – covariance – hyperspectral – mcmc – multivariate – unmixing

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

APA (6^{th} Edition):

Dranishnikov, D. A. (2014). Bayesian Hyperspectral Unmixing with Multivariate Beta Distributions. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046690

Chicago Manual of Style (16^{th} Edition):

Dranishnikov, Dmitri Alexander. “Bayesian Hyperspectral Unmixing with Multivariate Beta Distributions.” 2014. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0046690.

MLA Handbook (7^{th} Edition):

Dranishnikov, Dmitri Alexander. “Bayesian Hyperspectral Unmixing with Multivariate Beta Distributions.” 2014. Web. 22 Oct 2019.

Vancouver:

Dranishnikov DA. Bayesian Hyperspectral Unmixing with Multivariate Beta Distributions. [Internet] [Doctoral dissertation]. University of Florida; 2014. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0046690.

Council of Science Editors:

Dranishnikov DA. Bayesian Hyperspectral Unmixing with Multivariate Beta Distributions. [Doctoral Dissertation]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0046690

University of Florida

7. Fisher, Nicholas. A Kernel Approach to Learning a Neuron Model from Spike Train Data.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2010, University of Florida

URL: http://ufdc.ufl.edu/UFE0042012

► A spiking neuron is a principal component of the brain and the nervous system. Understanding the characteristics of a single neuron as well as the…
(more)

Subjects/Keywords: Approximation; Cell membranes; Histograms; Hyperplanes; Ions; Learning; Membrane potential; Modeling; Neurons; Synapses; classification, data, kernel, model, neuron, spike, spiking, time, train

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APA (6^{th} Edition):

Fisher, N. (2010). A Kernel Approach to Learning a Neuron Model from Spike Train Data. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0042012

Chicago Manual of Style (16^{th} Edition):

Fisher, Nicholas. “A Kernel Approach to Learning a Neuron Model from Spike Train Data.” 2010. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0042012.

MLA Handbook (7^{th} Edition):

Fisher, Nicholas. “A Kernel Approach to Learning a Neuron Model from Spike Train Data.” 2010. Web. 22 Oct 2019.

Vancouver:

Fisher N. A Kernel Approach to Learning a Neuron Model from Spike Train Data. [Internet] [Doctoral dissertation]. University of Florida; 2010. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0042012.

Council of Science Editors:

Fisher N. A Kernel Approach to Learning a Neuron Model from Spike Train Data. [Doctoral Dissertation]. University of Florida; 2010. Available from: http://ufdc.ufl.edu/UFE0042012

University of Florida

8. Cobb, James T. Sonar Image Modeling for Texture Discrimination and Classification.

Degree: PhD, Electrical and Computer Engineering, 2011, University of Florida

URL: http://ufdc.ufl.edu/UFE0043611

► High-resolution synthetic aperture sonar (SAS) systems yield finely detailedimages of sea bed environments. SAS image texture models must be capable ofrepresenting a wide variety of…
(more)

Subjects/Keywords: Imaging; Mathematical independent variables; Ocean floor; Parametric models; Pixels; Rock textures; Sand ripples; Sonar; Statistical models; Statistics; autocorrelation – expectation-maximization – k-distribution – segmentation – sonar

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APA (6^{th} Edition):

Cobb, J. T. (2011). Sonar Image Modeling for Texture Discrimination and Classification. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043611

Chicago Manual of Style (16^{th} Edition):

Cobb, James T. “Sonar Image Modeling for Texture Discrimination and Classification.” 2011. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0043611.

MLA Handbook (7^{th} Edition):

Cobb, James T. “Sonar Image Modeling for Texture Discrimination and Classification.” 2011. Web. 22 Oct 2019.

Vancouver:

Cobb JT. Sonar Image Modeling for Texture Discrimination and Classification. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0043611.

Council of Science Editors:

Cobb JT. Sonar Image Modeling for Texture Discrimination and Classification. [Doctoral Dissertation]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043611

University of Florida

9. Mcleod, Adam M. Learning Control Policies from Demonstration in Continuous Sensory and Action Space.

Degree: PhD, Electrical and Computer Engineering, 2015, University of Florida

URL: http://ufdc.ufl.edu/UFE0049418

► Learning to control a bipedal robot is a difficult control task. Learning to do so rapidly or automatically is even more difficult. This dissertation discusses…
(more)

Subjects/Keywords: Datasets; Learning; Learning rate; Lifelong learning; Machine learning; Mathematical vectors; Robotics; Robots; Sine waves; Walking; learning – machine

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

APA (6^{th} Edition):

Mcleod, A. M. (2015). Learning Control Policies from Demonstration in Continuous Sensory and Action Space. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0049418

Chicago Manual of Style (16^{th} Edition):

Mcleod, Adam M. “Learning Control Policies from Demonstration in Continuous Sensory and Action Space.” 2015. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0049418.

MLA Handbook (7^{th} Edition):

Mcleod, Adam M. “Learning Control Policies from Demonstration in Continuous Sensory and Action Space.” 2015. Web. 22 Oct 2019.

Vancouver:

Mcleod AM. Learning Control Policies from Demonstration in Continuous Sensory and Action Space. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0049418.

Council of Science Editors:

Mcleod AM. Learning Control Policies from Demonstration in Continuous Sensory and Action Space. [Doctoral Dissertation]. University of Florida; 2015. Available from: http://ufdc.ufl.edu/UFE0049418

University of Florida

10. Gurumoorthy,Karthik S. A Schrodinger Wave Mechanics Formalism for the Eikonal Problem and Its Associated Gradient Density Computation.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2011, University of Florida

URL: http://ufdc.ufl.edu/UFE0043099

Many computational techniques based on classical mechanics exist but surprisingly there isn't a concomitant
*Advisors/Committee Members: Banerjee, Arunava (committee chair), Ho, Jeffrey (committee member), Vemuri, Baba C (committee member), Gader, Paul D (committee member), Shabanov, Sergei (committee member).*

Subjects/Keywords: Approximation; Distance functions; Eikonal equation; Error rates; Fourier transformations; Mathematics; Quantum mechanics; Steepest descent method; Wave equations; Wave functions

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APA (6^{th} Edition):

S, G. (2011). A Schrodinger Wave Mechanics Formalism for the Eikonal Problem and Its Associated Gradient Density Computation. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043099

Chicago Manual of Style (16^{th} Edition):

S, Gurumoorthy,Karthik. “A Schrodinger Wave Mechanics Formalism for the Eikonal Problem and Its Associated Gradient Density Computation.” 2011. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0043099.

MLA Handbook (7^{th} Edition):

S, Gurumoorthy,Karthik. “A Schrodinger Wave Mechanics Formalism for the Eikonal Problem and Its Associated Gradient Density Computation.” 2011. Web. 22 Oct 2019.

Vancouver:

S G. A Schrodinger Wave Mechanics Formalism for the Eikonal Problem and Its Associated Gradient Density Computation. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0043099.

Council of Science Editors:

S G. A Schrodinger Wave Mechanics Formalism for the Eikonal Problem and Its Associated Gradient Density Computation. [Doctoral Dissertation]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043099

University of Florida

11. Horton, Joshua A. Normalized Maximum Likelihood on Variable-Length Sequence Datasets.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2014, University of Florida

URL: http://ufdc.ufl.edu/UFE0047146

► This work examines the minimal description length criterion and the normalized maximum likelihood distribution and derives extensions for applications in which data sequences are of…
(more)

Subjects/Keywords: Datasets; Language; Linguistics; Mathematical sequences; Modeling; Parametric models; Statistical models; Syllables; Topology; Words; hidden-markov-models – machine-learning – model-selection – normalized-maximum-likelihood

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

APA (6^{th} Edition):

Horton, J. A. (2014). Normalized Maximum Likelihood on Variable-Length Sequence Datasets. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0047146

Chicago Manual of Style (16^{th} Edition):

Horton, Joshua A. “Normalized Maximum Likelihood on Variable-Length Sequence Datasets.” 2014. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0047146.

MLA Handbook (7^{th} Edition):

Horton, Joshua A. “Normalized Maximum Likelihood on Variable-Length Sequence Datasets.” 2014. Web. 22 Oct 2019.

Vancouver:

Horton JA. Normalized Maximum Likelihood on Variable-Length Sequence Datasets. [Internet] [Doctoral dissertation]. University of Florida; 2014. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0047146.

Council of Science Editors:

Horton JA. Normalized Maximum Likelihood on Variable-Length Sequence Datasets. [Doctoral Dissertation]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0047146

University of Florida

12. Mazhar, Raazia. Optimized Dictionary Design and Classification Using the Matching Pursuits Dissimilarity Measure.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2009, University of Florida

URL: http://ufdc.ufl.edu/UFE0024309

► Discrimination-based classifiers differentiate between two classes by drawing a decision boundary between their data members in the feature domain. These classifiers are capable of correctly…
(more)

Subjects/Keywords: Approximation; Datasets; Information classification; Land mines; Learning; Learning modalities; Outliers; Signal processing; Signals; Test data; agglomeration, camp, classification, clustering, competitive, detection, dictionary, dissimilarity, enhanced, fuzzy, ksvd, learning, machine, matching, measure, outlier, prototype, pursuits

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

APA (6^{th} Edition):

Mazhar, R. (2009). Optimized Dictionary Design and Classification Using the Matching Pursuits Dissimilarity Measure. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0024309

Chicago Manual of Style (16^{th} Edition):

Mazhar, Raazia. “Optimized Dictionary Design and Classification Using the Matching Pursuits Dissimilarity Measure.” 2009. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0024309.

MLA Handbook (7^{th} Edition):

Mazhar, Raazia. “Optimized Dictionary Design and Classification Using the Matching Pursuits Dissimilarity Measure.” 2009. Web. 22 Oct 2019.

Vancouver:

Mazhar R. Optimized Dictionary Design and Classification Using the Matching Pursuits Dissimilarity Measure. [Internet] [Doctoral dissertation]. University of Florida; 2009. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0024309.

Council of Science Editors:

Mazhar R. Optimized Dictionary Design and Classification Using the Matching Pursuits Dissimilarity Measure. [Doctoral Dissertation]. University of Florida; 2009. Available from: http://ufdc.ufl.edu/UFE0024309

University of Florida

13. Glenn, Taylor C. Context-Dependent Detection in Hyperspectral Imagery.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2013, University of Florida

URL: http://ufdc.ufl.edu/UFE0046170

► Significant context information often exists in hyperspectral images, but the existing known-signature target detection techniques do not explicitly account for this fact and do not…
(more)

Subjects/Keywords: Algorithms; Change detection; Covariance; Datasets; False alarms; Matched filters; Pixels; Remote sensing; Signals; Statistics; bayesian – context-dependent – detection – fuzzy – hyperspectral

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

APA (6^{th} Edition):

Glenn, T. C. (2013). Context-Dependent Detection in Hyperspectral Imagery. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046170

Chicago Manual of Style (16^{th} Edition):

Glenn, Taylor C. “Context-Dependent Detection in Hyperspectral Imagery.” 2013. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0046170.

MLA Handbook (7^{th} Edition):

Glenn, Taylor C. “Context-Dependent Detection in Hyperspectral Imagery.” 2013. Web. 22 Oct 2019.

Vancouver:

Glenn TC. Context-Dependent Detection in Hyperspectral Imagery. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0046170.

Council of Science Editors:

Glenn TC. Context-Dependent Detection in Hyperspectral Imagery. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0046170

University of Florida

14. Close, Ryan Russell. Endmember and Proportion Estimation Using Physics-Based Macroscopic and Microscopic Mixture Models.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2011, University of Florida

URL: http://ufdc.ufl.edu/UFE0043582

► Methods of incorporating macroscopic and microscopic mixture models into hyperspectral image (HSI) endmember and proportion estimation is presented and discussed. These methods utilize the linear…
(more)

Subjects/Keywords: Albedo; Datasets; Estimate reliability; Estimation methods; Image processing; Modeling; Pixels; Proportions; Reflectance; Remote sensing; endmember – hyperspectral – macroscopic – microscopic – mixtures – nonlinear – physics-based – proportion – unmix

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APA (6^{th} Edition):

Close, R. R. (2011). Endmember and Proportion Estimation Using Physics-Based Macroscopic and Microscopic Mixture Models. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043582

Chicago Manual of Style (16^{th} Edition):

Close, Ryan Russell. “Endmember and Proportion Estimation Using Physics-Based Macroscopic and Microscopic Mixture Models.” 2011. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0043582.

MLA Handbook (7^{th} Edition):

Close, Ryan Russell. “Endmember and Proportion Estimation Using Physics-Based Macroscopic and Microscopic Mixture Models.” 2011. Web. 22 Oct 2019.

Vancouver:

Close RR. Endmember and Proportion Estimation Using Physics-Based Macroscopic and Microscopic Mixture Models. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0043582.

Council of Science Editors:

Close RR. Endmember and Proportion Estimation Using Physics-Based Macroscopic and Microscopic Mixture Models. [Doctoral Dissertation]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043582

University of Florida

15. Vanderkraats, Nathan. A Novel Probabilistic Lower Bound on Mutual Information Applied to a Category-Based Framework for Spike Train Discrimination.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2009, University of Florida

URL: http://ufdc.ufl.edu/UFE0041213

► We propose a framework by which the information transmission capacity of feedforward networks of spiking neurons can be measured for any discrete set of stimulus…
(more)

Subjects/Keywords: Auditory nerve; Distribution functions; Entropy; Harmonics; Mathematical vectors; Modeling; Neurons; Random variables; Signals; Statistics

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

APA (6^{th} Edition):

Vanderkraats, N. (2009). A Novel Probabilistic Lower Bound on Mutual Information Applied to a Category-Based Framework for Spike Train Discrimination. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0041213

Chicago Manual of Style (16^{th} Edition):

Vanderkraats, Nathan. “A Novel Probabilistic Lower Bound on Mutual Information Applied to a Category-Based Framework for Spike Train Discrimination.” 2009. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0041213.

MLA Handbook (7^{th} Edition):

Vanderkraats, Nathan. “A Novel Probabilistic Lower Bound on Mutual Information Applied to a Category-Based Framework for Spike Train Discrimination.” 2009. Web. 22 Oct 2019.

Vancouver:

Vanderkraats N. A Novel Probabilistic Lower Bound on Mutual Information Applied to a Category-Based Framework for Spike Train Discrimination. [Internet] [Doctoral dissertation]. University of Florida; 2009. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0041213.

Council of Science Editors:

Vanderkraats N. A Novel Probabilistic Lower Bound on Mutual Information Applied to a Category-Based Framework for Spike Train Discrimination. [Doctoral Dissertation]. University of Florida; 2009. Available from: http://ufdc.ufl.edu/UFE0041213

University of Florida

16. Yang, Ce. Spectral Analysis and Multispectral/Hyperspectral Imaging to Detect Blueberry Fruit Maturity Stages for Early Blueberry Yield Estimation.

Degree: PhD, Agricultural and Biological Engineering, 2013, University of Florida

URL: http://ufdc.ufl.edu/UFE0046320

► Blueberry industry has been increasingly important to both *Florida* and United States economically since 1990’s (USDA, 2012). Thanks to the friendly climate, blueberry harvesting window…
(more)

Subjects/Keywords: Blueberries; Fruits; Imaging; Maturity stage; Modeling; Pixels; Reflectance; Spectral bands; Spectroscopy; Wavelengths; blueberry – hyperspectral – imaging – multispectral – spectroscopy

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Yang, C. (2013). Spectral Analysis and Multispectral/Hyperspectral Imaging to Detect Blueberry Fruit Maturity Stages for Early Blueberry Yield Estimation. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046320

Chicago Manual of Style (16^{th} Edition):

Yang, Ce. “Spectral Analysis and Multispectral/Hyperspectral Imaging to Detect Blueberry Fruit Maturity Stages for Early Blueberry Yield Estimation.” 2013. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0046320.

MLA Handbook (7^{th} Edition):

Yang, Ce. “Spectral Analysis and Multispectral/Hyperspectral Imaging to Detect Blueberry Fruit Maturity Stages for Early Blueberry Yield Estimation.” 2013. Web. 22 Oct 2019.

Vancouver:

Yang C. Spectral Analysis and Multispectral/Hyperspectral Imaging to Detect Blueberry Fruit Maturity Stages for Early Blueberry Yield Estimation. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0046320.

Council of Science Editors:

Yang C. Spectral Analysis and Multispectral/Hyperspectral Imaging to Detect Blueberry Fruit Maturity Stages for Early Blueberry Yield Estimation. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0046320

University of Florida

17. Zhang, Xuping. Automatic Feature Learning and Parameter Estimation for Hidden Markov Models Using MCE and Gibbs Sampling.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2009, University of Florida

URL: http://ufdc.ufl.edu/UFE0041157

► Hidden Markov models (HMMs) are useful tools for landmine detection using Ground Penetrating Radar (GPR), as well as many other applications. The performance of HMMs…
(more)

Subjects/Keywords: Datasets; Feature extraction; Land mines; Learning; Learning modalities; Machine learning; Markov models; Neural networks; Parametric models; Principal components analysis; bayesian, classfication, convolution, feature, gaussian, gibbs, hmm, learning, mcmc, morphological, owa, sampling

Record Details Similar Records

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

APA (6^{th} Edition):

Zhang, X. (2009). Automatic Feature Learning and Parameter Estimation for Hidden Markov Models Using MCE and Gibbs Sampling. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0041157

Chicago Manual of Style (16^{th} Edition):

Zhang, Xuping. “Automatic Feature Learning and Parameter Estimation for Hidden Markov Models Using MCE and Gibbs Sampling.” 2009. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0041157.

MLA Handbook (7^{th} Edition):

Zhang, Xuping. “Automatic Feature Learning and Parameter Estimation for Hidden Markov Models Using MCE and Gibbs Sampling.” 2009. Web. 22 Oct 2019.

Vancouver:

Zhang X. Automatic Feature Learning and Parameter Estimation for Hidden Markov Models Using MCE and Gibbs Sampling. [Internet] [Doctoral dissertation]. University of Florida; 2009. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0041157.

Council of Science Editors:

Zhang X. Automatic Feature Learning and Parameter Estimation for Hidden Markov Models Using MCE and Gibbs Sampling. [Doctoral Dissertation]. University of Florida; 2009. Available from: http://ufdc.ufl.edu/UFE0041157

University of Florida

18. Heo, Gyeongyong. Robust kernel methods in context-dependent fusion.

URL: http://ufdc.ufl.edu/UFE0041144

► Combining classifiers, a common way to improve the performance of classification, has gained popularity in recent years. By combining classifiers, one can take advantage of…
(more)

Subjects/Keywords: Covariance; Cumulative distribution functions; Datasets; Eigenvectors; Error rates; Experimental results; Land mines; Mathematical vectors; Objective functions; Principal components analysis; clustering, context, fusion, fuzzy, kernel, landmine, pca, robustness, svm

Record Details Similar Records

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

APA (6^{th} Edition):

Heo, G. (2009). Robust kernel methods in context-dependent fusion. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0041144

Chicago Manual of Style (16^{th} Edition):

Heo, Gyeongyong. “Robust kernel methods in context-dependent fusion.” 2009. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0041144.

MLA Handbook (7^{th} Edition):

Heo, Gyeongyong. “Robust kernel methods in context-dependent fusion.” 2009. Web. 22 Oct 2019.

Vancouver:

Heo G. Robust kernel methods in context-dependent fusion. [Internet] [Doctoral dissertation]. University of Florida; 2009. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0041144.

Council of Science Editors:

Heo G. Robust kernel methods in context-dependent fusion. [Doctoral Dissertation]. University of Florida; 2009. Available from: http://ufdc.ufl.edu/UFE0041144

University of Florida

19. Ramachandran, Ganesan. Fast Physics-Based Methods for Wideband Electromagnetic Induction Data Analysis.

Degree: PhD, Electrical and Computer Engineering, 2010, University of Florida

URL: http://ufdc.ufl.edu/UFE0041627

► 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…
(more)

Subjects/Keywords: Datasets; Dielectric materials; Error rates; Estimation methods; Geometric angles; Information search; Land mines; Modeling; Parametric models; Sensors; electromagnetic, landmine, sparse, wideband

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

APA (6^{th} Edition):

Ramachandran, G. (2010). Fast Physics-Based Methods for Wideband Electromagnetic Induction Data Analysis. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0041627

Chicago Manual of Style (16^{th} Edition):

Ramachandran, Ganesan. “Fast Physics-Based Methods for Wideband Electromagnetic Induction Data Analysis.” 2010. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0041627.

MLA Handbook (7^{th} Edition):

Ramachandran, Ganesan. “Fast Physics-Based Methods for Wideband Electromagnetic Induction Data Analysis.” 2010. Web. 22 Oct 2019.

Vancouver:

Ramachandran G. Fast Physics-Based Methods for Wideband Electromagnetic Induction Data Analysis. [Internet] [Doctoral dissertation]. University of Florida; 2010. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0041627.

Council of Science Editors:

Ramachandran G. Fast Physics-Based Methods for Wideband Electromagnetic Induction Data Analysis. [Doctoral Dissertation]. University of Florida; 2010. Available from: http://ufdc.ufl.edu/UFE0041627

University of Florida

20. Deng, Qi. New Nonsmooth Convex Optimization Methods for Machine Learning.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2015, University of Florida

URL: http://ufdc.ufl.edu/UFE0049608

► Machine learning studies how to build models and develop algorithms that can learn from the data. Central to the machine learning area is the design…
(more)

Subjects/Keywords: Algorithms; Approximation; Averaging methods; Coordinate systems; Data smoothing; Datasets; Linear regression; Machine learning; Saddle points; Search engine optimization; learning – machine – optimization

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

APA (6^{th} Edition):

Deng, Q. (2015). New Nonsmooth Convex Optimization Methods for Machine Learning. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0049608

Chicago Manual of Style (16^{th} Edition):

Deng, Qi. “New Nonsmooth Convex Optimization Methods for Machine Learning.” 2015. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0049608.

MLA Handbook (7^{th} Edition):

Deng, Qi. “New Nonsmooth Convex Optimization Methods for Machine Learning.” 2015. Web. 22 Oct 2019.

Vancouver:

Deng Q. New Nonsmooth Convex Optimization Methods for Machine Learning. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0049608.

Council of Science Editors:

Deng Q. New Nonsmooth Convex Optimization Methods for Machine Learning. [Doctoral Dissertation]. University of Florida; 2015. Available from: http://ufdc.ufl.edu/UFE0049608

University of Florida

21. Bae, Jihye. Kernel Temporal Differences for Reinforcement Learning with Applications to Brain Machine Interfaces.

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

URL: http://ufdc.ufl.edu/UFE0045881

► Reinforcement learning brain machine interfaces (RLBMI) have been shown to be a promising avenue for practical implementations of BMIs. In the RLBMI, a computer agent…
(more)

Subjects/Keywords: Algorithms; Approximation; Decryption; Error rates; Experimentation; Learning; Learning modalities; Learning rate; Machine learning; Monkeys; learning

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

APA (6^{th} Edition):

Bae, J. (2013). Kernel Temporal Differences for Reinforcement Learning with Applications to Brain Machine Interfaces. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045881

Chicago Manual of Style (16^{th} Edition):

Bae, Jihye. “Kernel Temporal Differences for Reinforcement Learning with Applications to Brain Machine Interfaces.” 2013. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0045881.

MLA Handbook (7^{th} Edition):

Bae, Jihye. “Kernel Temporal Differences for Reinforcement Learning with Applications to Brain Machine Interfaces.” 2013. Web. 22 Oct 2019.

Vancouver:

Bae J. Kernel Temporal Differences for Reinforcement Learning with Applications to Brain Machine Interfaces. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0045881.

Council of Science Editors:

Bae J. Kernel Temporal Differences for Reinforcement Learning with Applications to Brain Machine Interfaces. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045881

University of Florida

22. Yuksel,Seniha E. Context-Based Classification Via Data-Dependent Mixtures of Logistic and Hidden Markov Model Classifiers.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2011, University of Florida

URL: http://ufdc.ufl.edu/UFE0043347

► This research addresses the problems encountered when designing classifiers for classes that contain multiple subclasses whose characteristics are dependent on the context. It is sometimes…
(more)

Subjects/Keywords: Datasets; Information classification; Land mines; Learning; Log integral function; Machine learning; Markov models; Neural networks; Time series; Time series models; based – classification – context – experts – hidden – hmm – markov – me – mhmme – mixture – model – variational – vmec

Record Details Similar Records

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

APA (6^{th} Edition):

E, Y. (2011). Context-Based Classification Via Data-Dependent Mixtures of Logistic and Hidden Markov Model Classifiers. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043347

Chicago Manual of Style (16^{th} Edition):

E, Yuksel,Seniha. “Context-Based Classification Via Data-Dependent Mixtures of Logistic and Hidden Markov Model Classifiers.” 2011. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0043347.

MLA Handbook (7^{th} Edition):

E, Yuksel,Seniha. “Context-Based Classification Via Data-Dependent Mixtures of Logistic and Hidden Markov Model Classifiers.” 2011. Web. 22 Oct 2019.

Vancouver:

E Y. Context-Based Classification Via Data-Dependent Mixtures of Logistic and Hidden Markov Model Classifiers. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0043347.

Council of Science Editors:

E Y. Context-Based Classification Via Data-Dependent Mixtures of Logistic and Hidden Markov Model Classifiers. [Doctoral Dissertation]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043347

University of Florida

23. Krekeler, Carolyn R. A Bayesian Based Graphical Model Framework for Estimation and Forecast of Stream Flow.

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

URL: http://ufdc.ufl.edu/UFE0043967

► For watershed monitoring and management, it is important to be able to predict with measurable accuracy the flow rates of major streams as a function…
(more)

Subjects/Keywords: Bayesian networks; Forecasting models; Forecasting techniques; Modeling; Probability forecasts; Rain; Spatial models; Statistical forecasts; Statistical models; Stream flow; bayesian – graphical – models – network – prediction

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

APA (6^{th} Edition):

Krekeler, C. R. (2012). A Bayesian Based Graphical Model Framework for Estimation and Forecast of Stream Flow. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043967

Chicago Manual of Style (16^{th} Edition):

Krekeler, Carolyn R. “A Bayesian Based Graphical Model Framework for Estimation and Forecast of Stream Flow.” 2012. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0043967.

MLA Handbook (7^{th} Edition):

Krekeler, Carolyn R. “A Bayesian Based Graphical Model Framework for Estimation and Forecast of Stream Flow.” 2012. Web. 22 Oct 2019.

Vancouver:

Krekeler CR. A Bayesian Based Graphical Model Framework for Estimation and Forecast of Stream Flow. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0043967.

Council of Science Editors:

Krekeler CR. A Bayesian Based Graphical Model Framework for Estimation and Forecast of Stream Flow. [Doctoral Dissertation]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0043967

University of Florida

24. Rummelt, Nicholas. Array Set Addressing Enabling Efficient Hexagonally Sampled Image Processing.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2010, University of Florida

URL: http://ufdc.ufl.edu/UFE0042319

► It has long been known that there are numerous advantages to sampling images hexagonally rather than rectangularly. However, due to various shortcomings of the addressing…
(more)

Subjects/Keywords: Butterflies; Cartesianism; Coordinate systems; Edge detection; Fast Fourier transformations; Fourier transformations; Image filters; Image processing; Pixels; Signals; addressing, grid, hexagonal, image, lattice, optimal, processing, sampling

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

APA (6^{th} Edition):

Rummelt, N. (2010). Array Set Addressing Enabling Efficient Hexagonally Sampled Image Processing. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0042319

Chicago Manual of Style (16^{th} Edition):

Rummelt, Nicholas. “Array Set Addressing Enabling Efficient Hexagonally Sampled Image Processing.” 2010. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0042319.

MLA Handbook (7^{th} Edition):

Rummelt, Nicholas. “Array Set Addressing Enabling Efficient Hexagonally Sampled Image Processing.” 2010. Web. 22 Oct 2019.

Vancouver:

Rummelt N. Array Set Addressing Enabling Efficient Hexagonally Sampled Image Processing. [Internet] [Doctoral dissertation]. University of Florida; 2010. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0042319.

Council of Science Editors:

Rummelt N. Array Set Addressing Enabling Efficient Hexagonally Sampled Image Processing. [Doctoral Dissertation]. University of Florida; 2010. Available from: http://ufdc.ufl.edu/UFE0042319

University of Florida

25. Smock, Brandon. A Perception-Centric Framework for Digital Timbre Manipulation in Music Composition.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2014, University of Florida

URL: http://ufdc.ufl.edu/UFE0046695

► In this work, a new framework is developed for the unrestricted manipulation of timbre in musical composition. Unlike other perceptual musical attributes such as pitch…
(more)

Subjects/Keywords: Auditory perception; Harmonics; Loudness; Musical instruments; Musical perception; Musical timbre; Signals; Sound; Sound pitch; Timbre; composition – instantaneous – mds – music – perception – space – timbre

Record Details Similar Records

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

APA (6^{th} Edition):

Smock, B. (2014). A Perception-Centric Framework for Digital Timbre Manipulation in Music Composition. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046695

Chicago Manual of Style (16^{th} Edition):

Smock, Brandon. “A Perception-Centric Framework for Digital Timbre Manipulation in Music Composition.” 2014. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0046695.

MLA Handbook (7^{th} Edition):

Smock, Brandon. “A Perception-Centric Framework for Digital Timbre Manipulation in Music Composition.” 2014. Web. 22 Oct 2019.

Vancouver:

Smock B. A Perception-Centric Framework for Digital Timbre Manipulation in Music Composition. [Internet] [Doctoral dissertation]. University of Florida; 2014. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0046695.

Council of Science Editors:

Smock B. A Perception-Centric Framework for Digital Timbre Manipulation in Music Composition. [Doctoral Dissertation]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0046695

University of Florida

26. Dhurandhar, Amit. Semi-Analytical Method for Analyzing Models and Model Selection Measures.

URL: http://ufdc.ufl.edu/UFE0024733

► Semi-Analytical Method for Analyzing Models and Model Selection Measures Considering the large amounts of data that is collected everyday in various domains such as health…
(more)

Subjects/Keywords: Covariance; Datasets; Decision trees; Distance functions; Error rates; Machine learning; Polynomials; Random variables; Sample size; Statistical discrepancies

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

APA (6^{th} Edition):

Dhurandhar, A. (2009). Semi-Analytical Method for Analyzing Models and Model Selection Measures. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0024733

Chicago Manual of Style (16^{th} Edition):

Dhurandhar, Amit. “Semi-Analytical Method for Analyzing Models and Model Selection Measures.” 2009. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0024733.

MLA Handbook (7^{th} Edition):

Dhurandhar, Amit. “Semi-Analytical Method for Analyzing Models and Model Selection Measures.” 2009. Web. 22 Oct 2019.

Vancouver:

Dhurandhar A. Semi-Analytical Method for Analyzing Models and Model Selection Measures. [Internet] [Doctoral dissertation]. University of Florida; 2009. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0024733.

Council of Science Editors:

Dhurandhar A. Semi-Analytical Method for Analyzing Models and Model Selection Measures. [Doctoral Dissertation]. University of Florida; 2009. Available from: http://ufdc.ufl.edu/UFE0024733

University of Florida

27. Vikas, Vishesh. Vestibular Dynamic Inclinometer and Measurement of Inclination Parameters.

Degree: PhD, Mechanical Engineering - Mechanical and Aerospace Engineering, 2011, University of Florida

URL: http://ufdc.ufl.edu/UFE0043745

► A human body displays a remarkable quality of maintaining both static and dynamic equilibrium for a rigid body in unstable equilibrium (modeled as an inverted…
(more)

Subjects/Keywords: Acceleration; Accelerometers; Angular acceleration; Angular velocity; Coordinate systems; Gyroscopes; Microelectromechanical systems; Resultants; Sensors; Simulations; inclinometer – robotics – sensor – vestibular

Record Details Similar Records

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

APA (6^{th} Edition):

Vikas, V. (2011). Vestibular Dynamic Inclinometer and Measurement of Inclination Parameters. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043745

Chicago Manual of Style (16^{th} Edition):

Vikas, Vishesh. “Vestibular Dynamic Inclinometer and Measurement of Inclination Parameters.” 2011. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0043745.

MLA Handbook (7^{th} Edition):

Vikas, Vishesh. “Vestibular Dynamic Inclinometer and Measurement of Inclination Parameters.” 2011. Web. 22 Oct 2019.

Vancouver:

Vikas V. Vestibular Dynamic Inclinometer and Measurement of Inclination Parameters. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0043745.

Council of Science Editors:

Vikas V. Vestibular Dynamic Inclinometer and Measurement of Inclination Parameters. [Doctoral Dissertation]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043745

University of Florida

28. Maissen, James R. Extensions of Group Actions and the Hilbert-Smith Conjecture.

Degree: PhD, Mathematics, 2013, University of Florida

URL: http://ufdc.ufl.edu/UFE0045160

► The Hilbert-Smith Conjecture proposes that every effective compact group action on a compact manifold is a Lie group. The conjecture is the generalization of Hilbert’s…
(more)

Subjects/Keywords: Compactification; Continuous functions; Distance functions; Homeomorphism; Mathematics; Quotients; Solenoids; Subrings; Topological theorems; Topology; action – conjecture – group – hilbert – smith – topology

Record Details Similar Records

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

APA (6^{th} Edition):

Maissen, J. R. (2013). Extensions of Group Actions and the Hilbert-Smith Conjecture. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045160

Chicago Manual of Style (16^{th} Edition):

Maissen, James R. “Extensions of Group Actions and the Hilbert-Smith Conjecture.” 2013. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0045160.

MLA Handbook (7^{th} Edition):

Maissen, James R. “Extensions of Group Actions and the Hilbert-Smith Conjecture.” 2013. Web. 22 Oct 2019.

Vancouver:

Maissen JR. Extensions of Group Actions and the Hilbert-Smith Conjecture. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0045160.

Council of Science Editors:

Maissen JR. Extensions of Group Actions and the Hilbert-Smith Conjecture. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045160

University of Florida

29. Nandan, Manu. Fast SVM Training Using Approximate Extreme Points.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2013, University of Florida

URL: http://ufdc.ufl.edu/UFE0046147

► Support vectors machines (SVMs) are widely applied machine learning algorithms that have many desirable characteristics. However, with the ever increasing size of datasets, it has…
(more)

Subjects/Keywords: Algorithms; Approximation; Datasets; Factorization; International conferences; Linear programming; Machine learning; Mathematical vectors; Matrices; Polynomials; approximate – extreme – kernels – svm

Record Details Similar Records

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

APA (6^{th} Edition):

Nandan, M. (2013). Fast SVM Training Using Approximate Extreme Points. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046147

Chicago Manual of Style (16^{th} Edition):

Nandan, Manu. “Fast SVM Training Using Approximate Extreme Points.” 2013. Doctoral Dissertation, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0046147.

MLA Handbook (7^{th} Edition):

Nandan, Manu. “Fast SVM Training Using Approximate Extreme Points.” 2013. Web. 22 Oct 2019.

Vancouver:

Nandan M. Fast SVM Training Using Approximate Extreme Points. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0046147.

Council of Science Editors:

Nandan M. Fast SVM Training Using Approximate Extreme Points. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0046147

30. Shuaibu, Mubarakat. Detection of Apple Marssonina Blotch Disease Using Hyperspectral Data.

Degree: MS, Agricultural and Biological Engineering, 2016, University of Florida

URL: http://ufdc.ufl.edu/UFE0050055

► Apple Marssonina blotch (AMB) is one of the most devastating apple diseases in the world, and it has caused huge economic losses to countries like…
(more)

Subjects/Keywords: Apples; Datasets; Diseases; Imaging; Leaves; Pixels; Reflectance; Spectral bands; Spectral reflectance; Vegetation; apple – blotch – diagnosis – hyperspectral – marssonina – reflectance – spectroradiometer

…*University* *of* *Florida* in Partial Fulfillment of the
Requirements for the Degree of Master of…

Record Details Similar Records

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

APA (6^{th} Edition):

Shuaibu, M. (2016). Detection of Apple Marssonina Blotch Disease Using Hyperspectral Data. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0050055

Chicago Manual of Style (16^{th} Edition):

Shuaibu, Mubarakat. “Detection of Apple Marssonina Blotch Disease Using Hyperspectral Data.” 2016. Masters Thesis, University of Florida. Accessed October 22, 2019. http://ufdc.ufl.edu/UFE0050055.

MLA Handbook (7^{th} Edition):

Shuaibu, Mubarakat. “Detection of Apple Marssonina Blotch Disease Using Hyperspectral Data.” 2016. Web. 22 Oct 2019.

Vancouver:

Shuaibu M. Detection of Apple Marssonina Blotch Disease Using Hyperspectral Data. [Internet] [Masters thesis]. University of Florida; 2016. [cited 2019 Oct 22]. Available from: http://ufdc.ufl.edu/UFE0050055.

Council of Science Editors:

Shuaibu M. Detection of Apple Marssonina Blotch Disease Using Hyperspectral Data. [Masters Thesis]. University of Florida; 2016. Available from: http://ufdc.ufl.edu/UFE0050055