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115
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MM
2004
ACM
124views Multimedia» more  MM 2004»
15 years 8 months ago
An online-optimized incremental learning framework for video semantic classification
This paper considers the problems of feature variation and concept uncertainty in typical learning-based video semantic classification schemes. We proposed a new online semantic c...
Jun Wu, Xian-Sheng Hua, HongJiang Zhang, Bo Zhang
141
Voted
LREC
2008
110views Education» more  LREC 2008»
15 years 4 months ago
Unsupervised and Domain Independent Ontology Learning: Combining Heterogeneous Sources of Evidence
Acquiring knowledge from the Web to build domain ontologies has become a common practice in the Ontological Engineering field. The vast amount of freely available information allo...
David Manzano-Macho, Asunción Gómez-...
158
Voted
TKDE
2011
479views more  TKDE 2011»
14 years 9 months ago
Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction
—Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feat...
Wei Zhang, Zhouchen Lin, Xiaoou Tang
173
Voted
CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
16 years 10 months ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)
SIGIR
2009
ACM
15 years 9 months ago
Named entity recognition in query
This paper addresses the problem of Named Entity Recognition in Query (NERQ), which involves detection of the named entity in a given query and classification of the named entity...
Jiafeng Guo, Gu Xu, Xueqi Cheng, Hang Li