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» Exploiting Unlabeled Data in Content-Based Image Retrieval
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CVPR
2010
IEEE
14 years 3 months ago
Semi-supervised Hashing for Scalable Image Retrieval
Large scale image search has recently attracted considerable attention due to easy availability of huge amounts of data. Several hashing methods have been proposed to allow approx...
Jun Wang, Sanjiv Kumar, Shih-Fu Chang
TIP
2010
155views more  TIP 2010»
13 years 5 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
MIR
2005
ACM
140views Multimedia» more  MIR 2005»
14 years 1 months ago
Multiple random walk and its application in content-based image retrieval
In this paper, we propose a transductive learning method for content-based image retrieval: Multiple Random Walk (MRW). Its basic idea is to construct two generative models by mea...
Jingrui He, Hanghang Tong, Mingjing Li, Wei-Ying M...
MM
2009
ACM
277views Multimedia» more  MM 2009»
14 years 2 months ago
Inferring semantic concepts from community-contributed images and noisy tags
In this paper, we exploit the problem of inferring images’ semantic concepts from community-contributed images and their associated noisy tags. To infer the concepts more accura...
Jinhui Tang, Shuicheng Yan, Richang Hong, Guo-Jun ...
TKDE
2008
378views more  TKDE 2008»
13 years 7 months ago
Modeling Image Data for Effective Indexing and Retrieval in Large General Image Databases
In this paper, we propose an image semantic model based on the knowledge and criteria in the field of linguistics and taxonomy. Our work bridges the "semantic gap" by sea...
Xiaoyan Li, Lidan Shou, Gang Chen, Tianlei Hu, Jin...