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» Combining Textual and Visual Features for Image Retrieval
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110
Voted
SIGIR
2008
ACM
14 years 9 months ago
Learning to reduce the semantic gap in web image retrieval and annotation
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...
Changhu Wang, Lei Zhang 0001, Hong-Jiang Zhang
EWCBR
2004
Springer
15 years 3 months ago
Feature Selection and Generalisation for Retrieval of Textual Cases
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...
Nirmalie Wiratunga, Ivan Koychev, Stewart Massie
IV
2000
IEEE
123views Visualization» more  IV 2000»
15 years 2 months ago
Content-Based Image Visualization
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...
Chaomei Chen, George Gagaudakis, Paul L. Rosin
101
Voted
ICIP
2000
IEEE
15 years 11 months ago
Combine User Defined Region-of-Interest and Spatial Layout for Image Retrieval
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...
Qi Tian, Ying Wu, Thomas S. Huang
MCAM
2007
Springer
112views Multimedia» more  MCAM 2007»
15 years 3 months ago
SIEVE - Search Images Effectively Through Visual Elimination
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...
Ying Liu, Dengsheng Zhang, Guojun Lu