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2010
ACM

Interactive learning of heterogeneous visual concepts with local features

8 years 8 months ago
Interactive learning of heterogeneous visual concepts with local features
In the context of computer-assisted plant identification we are facing challenging information retrieval problems because of the very high within-class variability and of the limited number of training examples. To address these problems, we suggest a new interactive learning approach that combines similarity-based retrieval and re-ranking by SVM using local feature distributions. This approach leads to improved sample selection, allowing to obtain better results. Categories and Subject Descriptors: H.3.3 [Information Systems]: Multimedia Information Search and Retrieval; H.3.1 [Information Storage and Retrieval]: Content Analysis and Indexing methods. General Terms: Algorithms.
Wajih Ouertani, Michel Crucianu, Nozha Boujemaa
Added 29 Jan 2011
Updated 29 Jan 2011
Type Journal
Year 2010
Where MM
Authors Wajih Ouertani, Michel Crucianu, Nozha Boujemaa
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