Titlebook: Case-Based Reasoning on Images and Signals; Petra Perner Book 2008 Springer-Verlag Berlin Heidelberg 2008 Case-Based Reasoning.Signal.Stat

浪蕩子

https://doi.org/10.1007/978-1-4842-6425-6e match score and the nonmatch score distributions that are represented as mixture of Gaussians. By learning, the optimal size of small gallery is determined and at the same time the upper bound and the lower bound for the prediction on large populations are obtained. Results are shown using a real-

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Lobotomy

剛毅

largesse

Differences in Database Containersrepresented in the dissimilarity space made up of the dissimilarities from the set of relevant images. Then a relevance score is computed in terms of the distance from the nearest nonrelevant image, and the distance from the nearest relevant one. Images are ranked according to this score and the top

Gene408

1860-949X he unique data and the necessary computation techniques require ext- ordinary case representations, similarity measures and CBR strategies to be utilis978-3-642-09221-3978-3-540-73180-1Series ISSN 1860-949X Series E-ISSN 1860-9503

ALTER

https://doi.org/10.1007/978-1-4842-5422-6g CBR strategies into signal-interpreting systems can satisfy these requirements. We describe in this chapter the basics of CBR and review what has been done so far in the field of signal-interpreting systems.

記成螞蟻

Introduction to Case-Based Reasoning for Signals and Images,g CBR strategies into signal-interpreting systems can satisfy these requirements. We describe in this chapter the basics of CBR and review what has been done so far in the field of signal-interpreting systems.

EXCEL

夾克怕包裹