arboretum 发表于 2025-3-23 10:20:54

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滋养 发表于 2025-3-23 17:21:24

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极力证明 发表于 2025-3-23 21:28:09

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resuscitation 发表于 2025-3-23 23:21:00

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photophobia 发表于 2025-3-24 04:20:59

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猜忌 发表于 2025-3-24 07:10:25

Registration, Matching, and Recognition,e instantiated to intensity distributions. Therefore, image registration can be posed as finding the (constrained) transformation that holds the maximal dependency between distributions. This rationale opens the door to the quest for new measures rooted in mutual information.

鸣叫 发表于 2025-3-24 13:46:28

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APEX 发表于 2025-3-24 14:59:45

Feature Selection and Transformation,undant, and some could introduce noise, or be irrelevant. In some problems the number of features is very high and their dimensionality has to be reduced in order to make the problem tractable. In other problems feature selection provides new knowledge about the data classes. For example, in gene se

不如乐死去 发表于 2025-3-24 19:23:28

Classifier Design, building unique but deep trees, in favor of a bunch of shallow trees. This is the keypoint of the chapter, the emergence of ., complex classifiers built in the aggregation/combination of simpler ones, and the role of IT in their design. In this regard, the method adapted to images is particularly i

Generalize 发表于 2025-3-25 02:40:54

978-1-4471-5693-2Springer-Verlag London Ltd., part of Springer Nature 2009
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查看完整版本: Titlebook: Information Theory in Computer Vision and Pattern Recognition; Francisco Escolano,Pablo Suau,Boyán Bonev Textbook 2009 Springer-Verlag Lon