期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：6
页码：12067
DOI：10.15680/IJIRSET.2017.0606267
出版社：S&S Publications
摘要：This is a new technology to support scalable content-based image retrieval (CBIR]), hashinghas been recently been focused and future directions of research domain. In this paper, we propose a uniqueunsupervised visual hashing approach called semantic-assisted visual hashing (SAVH). Distinguished fromsemi-supervised and supervised visual hashing, its core idea emphatically extracts the rich semantics latentlyembedded in auxiliary texts of images to boost the effectiveness of visual hashing without any explicitsemantic labels. To expand the reach, a unsupervised framework is advanced to learn hash codes bysimultaneously preserving visual similarities of images, integrating the semantic assistance from texts onmodeling high relationships of inter images and defining the correlations between images and shared contents.
关键词：CBIR; Semantic Assistance; Visual Hashing; Text Auxiliaries; Unsupervised Learning.
