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» Content-Based Image Retrieval Using Multiple Representations
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ICPR
2000
IEEE
15 years 10 months ago
Feature Relevance Learning with Query Shifting for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Douglas R. Heisterkamp, Jing Peng, H. K. Dai
VISUAL
2000
Springer
15 years 1 months ago
Shape Description for Content-Based Image Retrieval
Abstract. The present work is focused on a global image characterization based on a description of the 2D displacements of the different shapes present in the image, which can be e...
Edoardo Ardizzone, Antonio Chella, Roberto Pirrone
ERCIMDL
2006
Springer
158views Education» more  ERCIMDL 2006»
15 years 1 months ago
A Content-Based Image Retrieval Service for Archaeology Collections
Archeological sites have heterogeneous information ranging from different artifacts, image data, geo-spatial information, chronological data, and other relevant metadata. ETANA-DL,...
Naga Srinivas Vemuri, Ricardo da Silva Torres, Rao...
ISM
2008
IEEE
108views Multimedia» more  ISM 2008»
15 years 4 months ago
Optimization of Content-Based Image Retrieval Functions
Feature extraction and similarity measurement are two important operations in content-based image retrieval systems. We optimize and vectorize typical feature extraction algorithm...
Asadollah Shahbahrami, Ben H. H. Juurlink
ICASSP
2007
IEEE
15 years 4 months ago
Integrating Relevance Feedback in Boosting for Content-Based Image Retrieval
Many content-based image retrieval applications suffer from small sample set and high dimensionality problems. Relevance feedback is often used to alleviate those problems. In thi...
Jie Yu, Yijuan Lu, Yuning Xu, Nicu Sebe, Qi Tian