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» Learning Local Image Descriptors
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KDD
2007
ACM
159views Data Mining» more  KDD 2007»
15 years 11 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
MM
2009
ACM
187views Multimedia» more  MM 2009»
15 years 3 months ago
Convex experimental design using manifold structure for image retrieval
Content Based Image Retrieval (CBIR) has become one of the most active research areas in computer science. Relevance feedback is often used in CBIR systems to bridge the semantic ...
Lijun Zhang, Chun Chen, Wei Chen, Jiajun Bu, Deng ...
KDD
2000
ACM
162views Data Mining» more  KDD 2000»
15 years 2 months ago
Data Mining from Functional Brain Images
Recent advances in functional brain imaging enable identication of active areas of a brain performing a certain function. Induction of logical formulas describing relations betwee...
Mitsuru Kakimoto, Chie Morita, Yoshiaki Kikuchi, H...
MIR
2005
ACM
141views Multimedia» more  MIR 2005»
15 years 4 months ago
A mutual semantic endorsement approach to image retrieval and context provision
Learning semantics from annotated images to enhance content-based retrieval is an important research direction. In this paper, annotation data are assumed available for only a sub...
Jia Li
MIR
2005
ACM
140views Multimedia» more  MIR 2005»
15 years 4 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...