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Abstract: User-defined classes in large generalist image databases are often composed of several groups of images and span very di#erent scales in the space of low-level visual descriptors. The interactive retrieval of such image classes is then very di#cult. To address this challenge, we propose and evaluate here two general improvements of SVM-based relevance feedback methods. First, to optimize the transfer of information between the user and the system, we focus on the criterion employed by the... (Update)
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BibTeX entry: (Update)
@misc{ ferecatu-retrieval,
author = "Marin Ferecatu and Michel Crucianu and et al.",
title = "Retrieval of Difficult Image Classes Using SVM-Based Relevance Feedback",
url = "citeseer.ist.psu.edu/726273.html" }
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