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» Feature selection for content-based image retrieval
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ICPR
2000
IEEE
16 years 8 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
164
Voted
KDD
2000
ACM
116views Data Mining» more  KDD 2000»
15 years 11 months ago
Learning Feature Weights from User Behavior in Content-Based Image Retrieval
Henning Müller, Wolfgang Müller 0002, Da...
142
Voted
JACIII
2007
72views more  JACIII 2007»
15 years 7 months ago
A Feature Vector Approach for Inter-Query Learning for Content-Based Image Retrieval
Kien-Ping Chung, Chun Che Fung
170
Voted
PAMI
2002
125views more  PAMI 2002»
15 years 7 months ago
A Region-Based Fuzzy Feature Matching Approach to Content-Based Image Retrieval
Yixin Chen, James Ze Wang
229
Voted
CSIE
2009
IEEE
16 years 2 months ago
Evaluating Clustering Algorithms: Cluster Quality and Feature Selection in Content-Based Image Clustering
The paper presents an evaluation of four clustering algorithms: k-means, average linkage, complete linkage, and Ward’s method, with the latter three being different hierarchical...
Mesfin Sileshi, Björn Gambäck