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» Textural Features and Relevance Feedback for Image Retrieval
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ETRA
2010
ACM
197views Biometrics» more  ETRA 2010»
15 years 6 months ago
Image ranking with implicit feedback from eye movements
In order to help users navigate an image search system, one could provide explicit information on a small set of images as to which of them are relevant or not to their task. Thes...
David R. Hardoon, Kitsuchart Pasupa
CVPR
2005
IEEE
15 years 5 months ago
Mapping Low-Level Features to High-Level Semantic Concepts in Region-Based Image Retrieval
In this a novel supervised learning method is proposed to map low-level visualfeatures to high-level semantic conceptsfor region-based image retrieval. The contributions of thispa...
Wei Jiang, Kap Luk Chan, Mingjing Li, HongJiang Zh...
105
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MM
2005
ACM
171views Multimedia» more  MM 2005»
15 years 5 months ago
Semantic manifold learning for image retrieval
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...
Yen-Yu Lin, Tyng-Luh Liu, Hwann-Tzong Chen
ICPR
2006
IEEE
16 years 26 days ago
Illumination Invariant Texture Retrieval
Two fast illumination invariant image retrieval methods for scenes comprising textured objects with variable illumination are introduced. Both methods are based on texture gradien...
Michal Haindl, Pavel Vacha