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FRAME: Filters, Random fields, and Minimax Entropy - Towards a Unified Theory for Texture Modeling.

, , and . CVPR, page 686-693. IEEE Computer Society, (1996)

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The Red Book of Varieties and Schemes, and . Lecture Notes in Mathematics Springer Berlin / Heidelberg, (2004)Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling., , and . Int. J. Comput. Vis., 27 (2): 107-126 (1998)Minimax Entropy Principle and Its Application to Texture Modeling., , and . Neural Comput., 9 (8): 1627-1660 (1997)Introduction by Guest Editors., , and . Int. J. Comput. Vis., 41 (1/2): 7 (2001)Texture Segmentation by Minimizing Vector-Valued Energy Functionals: The Coupled-Membrane Model., , and . ECCV, volume 588 of Lecture Notes in Computer Science, page 165-173. Springer, (1992)Occlusion models for natural images: A statistical study of a scale-invariant dead leaves model, , and . International Journal of Computer Vision, 41 (1-2): 35--59 (2001)Mathematical Theories of Shape: do they model perception?. Proc. Conference, Soc. Photo-optical & Ind. Engineers (SPIE), (1991)GRADE: Gibbs Reaction and Diffusion Equation., and . ICCV, page 847-856. IEEE Computer Society, (1998)FRAME: Filters, Random fields, and Minimax Entropy - Towards a Unified Theory for Texture Modeling., , and . CVPR, page 686-693. IEEE Computer Society, (1996)Bayesian Pot-Assembly from Fragments as Problems in Perceptual-Grouping and Geometric-Learning., , , , , , , , , and 6 other author(s). ICPR (3), page 297-302. IEEE Computer Society, (2002)