Pattern Retrieval in Large Image Databases Using Multiscale Coarse-to-Fine Cascaded Active Learning

Pattern retrieval is a fundamental challenge in machine learning but is often subject to the problem of gathering enough labeled examples of the target pattern, and also to the computational complexity inherent to the training and the evaluation of complex classifier functions on large databases. In...

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Vydané v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 7; číslo 4; s. 1127 - 1141
Hlavní autori:	Blanchart, Pierre, Ferecatu, Marin, Cui, Shiyong, Datcu, Mihai
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.04.2014 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Active learning Algorithms coarse-to-fine testing Computer Science Context Detectors Image databases multiple instance learning (MIL) pattern retrieval Remote sensing Support vector machines support vector machines (SVMs) Training active learning apprentissage d'instance multiple support vector machines coarse-to-fine testing multiple instance learning apprentissage actif test de gros-de-fine Récupération du modèle Pattern retrieval
ISSN:	1939-1404, 2151-1535
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