Using Dual Cascading Learning Frameworks for Image Indexing
نویسندگان
چکیده
To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images into semantic categories based on trained pattern classifiers have become active research trends. In this paper, we present dual cascading learning frameworks that extract and combine intraimage and inter-class semantics for image indexing and re-
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تاریخ انتشار 2003