Modified one-class support vector machine for content-based image retrieval with relevance feedback

Image retrieval via traditional Content-Based Image Retrieval (CBIR) often incurs the semantic gap problem—non-correlation of image retrieval results with human semantic interpretation of images. In this paper, Relevance Feedback (RF) mechanism was incorporated into a traditional Query by Visual Exa...

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書誌詳細

出版年:	Cogent Engineering
主要な著者:	Oluwole A. Adegbola, David O. Aborisade, Segun I. Popoola, Olatide A. Amole, Aderemi A. Atayero
フォーマット:	論文
言語:	英語
出版事項:	Taylor & Francis Group 2018-01-01
主題:	content-based image retrieval one-class support vector machine relevance feedback principal component analysis visual descriptors
オンライン･アクセス:	http://dx.doi.org/10.1080/23311916.2018.1541702