Combining Long Term and Short Term Learning for Improved Cbir (content Based Image Retrieval)
نویسنده
چکیده
Content Based Image Retrival needs relevance feedback to obtain more accurate results. By building a repository with KBDA, very good results may be obtained with the use of a Query Semantic Feature Vector.
منابع مشابه
Long term learning in image retrieval systems using case based reasoning
Relevance feedback is a powerful tool emerged to boost the retrieval performance of content based image retrieval (CBIR) systems. Short term learning (STL) and long term learning (LTL) are two learning methods of relevance feedback scheme. This paper presents a long term learning method in CBIR systems adopting case based reasoning (CBR) which is called Casebased LTL (CB-LTL). The method has tw...
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