We study in this paper the problem of bridging the semantic gap between low-level image features and high-level semantic concepts, which is the key hindrance in content-based imag...
Textual CBR systems solve problems by reusing experiences that are in textual form. Knowledge-rich comparison of textual cases remains an important challenge for these systems. How...
The proliferation of content-based image retrieval techniques has highlighted the need to understand the relationship between image clustering based on low-Ievel imagefeatures and...
Content-Based Image Retrieval (CBIR) is one of the most active research areas in recent years. Many visual feature representations have been explored and many systems built. Howev...
Existing Web image search engines index images by textual descriptions including filename, image caption, surrounding text, etc. However, the textual description available on the W...