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- W2364775286 abstract "Relevance feedback technique is an important approach for image retrieval.A novel relevance feedback algorithm is presented based on Support Vector Machine(SVM) in content-based image retrieval system,and MPEG-7 edge histogram.During the retrieval process,users can mark positive sample images similar to the query image.Then the algorithm constructs a SVM classifier,which uses the updated training samples.The performances of SVMs with different kernel functions have been tested and compared.The RBF function has higher precision of retrieval than others.Experiments are carried out on a database of 10000 images.It shows that more images relevant to the query can be found efficiently by the retrieval process.It also shows the generalization ability of SVM under the conditions of limited training samples." @default.
- W2364775286 created "2016-06-24" @default.
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- W2364775286 date "2009-01-01" @default.
- W2364775286 modified "2023-09-24" @default.
- W2364775286 title "A SVM Based Relevance Feedback Algorithm for Image Retrieval" @default.
- W2364775286 hasPublicationYear "2009" @default.
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