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Titlebook: Machine Learning Techniques for Multimedia; Case Studies on Orga Matthieu Cord,Pádraig Cunningham Book 2008 Springer-Verlag Berlin Heidelbe

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樓主: Daguerreotype
31#
發(fā)表于 2025-3-26 22:17:37 | 只看該作者
Online Content-Based Image Retrieval Using Active Learningosed to handle multimedia applications. The purpose of this chapter is to present an overview of the online image retrieval systems based on supervised classification techniques. This chapter also provides algorithms in a statistical framework to extend active learning strategies for online content-based image retrieval.
32#
發(fā)表于 2025-3-27 04:45:50 | 只看該作者
33#
發(fā)表于 2025-3-27 08:43:11 | 只看該作者
34#
發(fā)表于 2025-3-27 11:33:48 | 只看該作者
35#
發(fā)表于 2025-3-27 16:43:29 | 只看該作者
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發(fā)表于 2025-3-27 21:15:07 | 只看該作者
37#
發(fā)表于 2025-3-27 22:02:19 | 只看該作者
Machine Learning Techniques for Multimedia978-3-540-75171-7Series ISSN 1611-2482 Series E-ISSN 2197-6635
38#
發(fā)表于 2025-3-28 05:09:52 | 只看該作者
https://doi.org/10.1007/978-3-540-75171-7Dimensionsreduktion; biometrics; classification; clustering; cognition; database; decision theory; learning
39#
發(fā)表于 2025-3-28 08:31:17 | 只看該作者
1611-2482 analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic l978-3-642-44362-6978-3-540-75171-7Series ISSN 1611-2482 Series E-ISSN 2197-6635
40#
發(fā)表于 2025-3-28 12:34:02 | 只看該作者
Conservative Learning for Object Detectors we are very confident about our decision. Applying this update rules, an incrementally better classifier is obtained without any user interaction. Moreover, an already trained classifier can be retrained online and can therefore easily be adapted to a completely different scene. We demonstrate the
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