Mendicant
发表于 2025-3-26 22:17:37
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.
Valves
发表于 2025-3-27 04:45:50
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现实
发表于 2025-3-27 08:43:11
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Accolade
发表于 2025-3-27 11:33:48
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陶瓷
发表于 2025-3-27 16:43:29
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Ige326
发表于 2025-3-27 21:15:07
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Coronation
发表于 2025-3-27 22:02:19
Machine Learning Techniques for Multimedia978-3-540-75171-7Series ISSN 1611-2482 Series E-ISSN 2197-6635
搏斗
发表于 2025-3-28 05:09:52
https://doi.org/10.1007/978-3-540-75171-7Dimensionsreduktion; biometrics; classification; clustering; cognition; database; decision theory; learning
Inclement
发表于 2025-3-28 08:31:17
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
思考
发表于 2025-3-28 12:34:02
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