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Pattern recognition / Segmentation / Mixture model / Minimum description length / Generative model / Unsupervised learning / Expectation–maximization algorithm / Statistical classification / Supervised learning / Statistics / Machine learning / Cluster analysis


Probabilistic Classification of Image Regions using Unsupervised and Supervised Learning
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Document Date: 2010-06-01 18:49:42

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File Size: 648,68 KB

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City

Rochester / Divergence / /

Company

Springer-Verlag Inc. / Oxford University Press / Neural Networks / Eastman Kodak Company / BT / Intelligent Robotics Systems / Microsoft / /

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Facility

University of Washington / Carnegie Mellon University / The Robotics Institute / Michigan State University / /

IndustryTerm

generic image understanding applications / steel gate / online soft clustering applications / /

NaturalFeature

KLD falls / /

Organization

University of Washington / Michigan State University / Robotics Institute / USA Imaging Science and Technology Lab / Department of Statistics / Carnegie Mellon University / Pittsburgh / Oxford University / IEEE Trans Pattern Analysis Machine Intelligence / /

Person

Goksel Dedeoglu / Zhao Hui Sun / Amit Singhal / Gabor Wavelets / Daniel Huber / /

Position

Gaussian generative model for the data / first author / representative / General / /

Technology

simulation / Image Processing / EM algorithm / /

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