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» Feature selection for content-based image retrieval
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ICIP
1999
IEEE
14 years 9 months ago
Water-Filling: A Novel Way for Image Structural Feature Extraction
The performance of a content based image retrieval (CBIR) system is inherently constrained by the features adopted to represent the images in the database. In this paper, a new ap...
Xiang Sean Zhou, Yong Rui, Thomas S. Huang
ICPR
2010
IEEE
13 years 5 months ago
Unsupervised Image Retrieval with Similar Lighting Conditions
In this work a new method to retrieve images with similar lighting conditions is presented. It is based on automatic clustering and automatic indexing. Our proposal belongs to Con...
J. Felix Serrano, Carlos Avilés, Humberto S...
ISBI
2009
IEEE
14 years 2 months ago
Bridging the Semantic Gap Using Ranking Svm for Image Retrieval
One of the main challenges for Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings between the high-level semantic concepts and the low-level visual features in...
Haiying Guan, Sameer Antani, L. Rodney Long, Georg...
CLEF
2010
Springer
13 years 8 months ago
RGU at ImageCLEF2010 Wikipedia Retrieval Task
Abstract. This working notes paper describes our first participation in the ImageCLEF2010 Wikipedia Retrieval Task[1]. In this task, we mainly test our Quantum Theory inspired retr...
Jun Wang, Dawei Song, Leszek Kaliciak
ICDE
2006
IEEE
191views Database» more  ICDE 2006»
14 years 9 months ago
Query Decomposition: A Multiple Neighborhood Approach to Relevance Feedback Processing in Content-based Image Retrieval
Today's Content-Based Image Retrieval (CBIR) techniques are based on the "k-nearest neighbors" (kNN) model. They retrieve images from a single neighborhood using lo...
Kien A. Hua, Ning Yu, Danzhou Liu