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MM
2004
ACM
124views Multimedia» more  MM 2004»
15 years 9 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
159
Voted
LREC
2008
110views Education» more  LREC 2008»
15 years 5 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-...
TKDE
2011
479views more  TKDE 2011»
14 years 11 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
CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
16 years 11 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 10 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