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CVPR
2005
IEEE
13 years 10 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...
ICMCS
2006
IEEE
161views Multimedia» more  ICMCS 2006»
13 years 10 months ago
Improved Similarity-Based Online Feature Selection in Region-Based Image Retrieval
To bridge the gap between high level semantic concepts and low level visual features in content-based image retrieval (CBIR), online feature selection is really required. An effec...
Fei Li, Qionghai Dai, Wenli Xu
MMM
2005
Springer
159views Multimedia» more  MMM 2005»
13 years 10 months ago
Region-Based Image Retrieval with High-Level Semantic Color Names
Performance of traditional content-based image retrieval systems is far from user’s expectation due to the ‘semantic gap’ between low-level visual features and the richness ...
Ying Liu, Dengsheng Zhang, Guojun Lu, Wei-Ying Ma
CVPR
2004
IEEE
14 years 6 months ago
Hidden Semantic Concept Discovery in Region Based Image Retrieval
This paper addresses Content Based Image Retrieval (CBIR), focusing on developing a hidden semantic concept discovery methodology to address effective semanticsintensive image ret...
Ruofei Zhang, Zhongfei (Mark) Zhang
KES
2006
Springer
13 years 4 months ago
M-OntoMat-Annotizer: Image Annotation Linking Ontologies and Multimedia Low-Level Features
Annotations of multimedia documents typically have been pursued in two different directions. Either previous approaches have focused on low level descriptors, such as dominant colo...
Kosmas Petridis, Dionysios Anastasopoulos, Carsten...