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» Features for image retrieval: an experimental comparison
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TKDE
2008
195views more  TKDE 2008»
15 years 6 months ago
Learning a Maximum Margin Subspace for Image Retrieval
One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
Xiaofei He, Deng Cai, Jiawei Han
MMDB
2003
ACM
132views Multimedia» more  MMDB 2003»
15 years 11 months ago
Image database retrieval utilizing affinity relationships
Recent research effort in Content-Based Image Retrieval (CBIR) focuses on bridging the gap between low-level features and highlevel semantic contents of images as this gap has bec...
Mei-Ling Shyu, Shu-Ching Chen, Min Chen, Chengcui ...
PAKDD
2009
ACM
263views Data Mining» more  PAKDD 2009»
16 years 28 days ago
Spatial Weighting for Bag-of-Visual-Words and Its Application in Content-Based Image Retrieval
It is a challenging and important task to retrieve images from a large and highly varied image data set based on their visual contents. Problems like how to fill the semantic gap b...
Xin Chen, Xiaohua Hu, Xiajiong Shen
PCM
2005
Springer
107views Multimedia» more  PCM 2005»
15 years 11 months ago
Salient Feature Selection for Visual Concept Learning
Abstract. Image classification could be treated as an effective solution to enable keyword-based semantic image retrieval. In this paper, we propose a novel image classification...
Feng Xu, Lei Zhang, Yu-Jin Zhang, Wei-Ying Ma
SPIESR
1998
195views Database» more  SPIESR 1998»
15 years 7 months ago
Relevance Feedback Techniques in Interactive Content-Based Image Retrieval
Content-Based Image Retrieval (CBIR) has become one of the most active research areas in the past few years. Many visual feature representations have been explored and many system...
Yong Rui, Thomas S. Huang, Sharad Mehrotra