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论文类型：会议论文

发表时间：2014-06-29

收录刊物：EI、Scopus

卷号：2015-March

期号：March

页面范围：1010-1013

摘要：This paper presents a new relevance feedback scheme, which incorporates Extreme Learning Machine (ELM) to content-based image retrieval (CBIR) with relevance feedback. Relevance feedback schemes based on Support Vector Machine (SVM) have been proposed in previous paper. However, the performance of the schemes are often poor which is caused by the low speed of SVM algorithm in high dimension data. To overcome the problem, ELM is applied to construct a classifier for relevance feedback instead of Support Vector Machine (SVM) which has been used in CBIR. Due to the faster speed and the higher accuracy of ELM algorithm, we can achieve better performance with the proposed scheme in image retrieval. Our experiments also show that it is feasible to incorporate ELM with relevance feedback for CBIR. ? 2014 IEEE.