Image Navigation: A Massively Interactive Model for Similarity Retrieval of Images
International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Interactive Image Retrieval in a Fuzzy Framework
WILF '09 Proceedings of the 8th International Workshop on Fuzzy Logic and Applications
Content-based image retrieval using visually significant point features
Fuzzy Sets and Systems
Image retrieval using fuzzy relevance feedback and validation with MPEG-7 content descriptors
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Interactive image retrieval with wavelet features
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
Interactive content based image retrieval using ripplet transform and fuzzy relevance feedback
PerMIn'12 Proceedings of the First Indo-Japan conference on Perception and Machine Intelligence
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Relevance feedback is a powerful technique for content-based image retrieval. Many parameter estimation approaches have been proposed for relevance feedback. However, most of them have only utilized information of the relevant retrieved images, and have given up, or have not made great use of information of the irrelevant retrieved images. This paper presents a novel approach to update the interweights of integrated probability function by using the information of both relevant and irrelevant retrieved images. Experimental results have shown the effectiveness and robustness of our proposed approach, especially in the situation of no relevant retrieved images.