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» Boosting Image Retrieval
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ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
14 years 1 months ago
Update Relevant Image Weights for Content-Based Image Retrieval using Support Vector Machines
Relevance feedback [1] has been a powerful tool for interactive Content-Based Image Retrieval (CBIR). During the retrieval process, the user selects the most relevant images and p...
Qi Tian, Pengyu Hong, Thomas S. Huang
CLEF
2010
Springer
13 years 10 months ago
ImageCLEF 2010 Modality Classification in Medical Image Retrieval: Multiple Feature Fusion with Normalized Kernel Function
Abstract. In this paper, we describe an approach for the automatic modality classification in medical image retrieval task of the 2010 CLEF cross-language image retrieval campaign ...
Xian-Hua Hanand Yen-Wei Chen
ESWA
2008
173views more  ESWA 2008»
13 years 9 months ago
Image semantics discovery from web pages for semantic-based image retrieval using self-organizing maps
Traditional content-based image retrieval (CBIR) systems often fail to meet a user's need due to the `semantic gap' between the extracted features of the systems and the...
Hsin-Chang Yang, Chung-Hong Lee
ICANN
2009
Springer
14 years 3 months ago
Modelling Image Complexity by Independent Component Analysis, with Application to Content-Based Image Retrieval
Abstract. Estimating the degree of similarity between images is a challenging task as the similarity always depends on the context. Because of this context dependency, it seems qui...
Jukka Perkiö, Aapo Hyvärinen
ICMCS
1999
IEEE
139views Multimedia» more  ICMCS 1999»
14 years 1 months ago
Image Indexing and Retrieval Using Image-Derived, Geometrically and Illumination Invariant Features
In this paper, we propose novel image-derived features for image indexing and retrieval in digital library applications. The new features capture the intrinsic geometry and color ...
Ronald-Bryan O. Alferez, Yuan-Fang Wang