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» Feature Extraction base on Local Maximum Margin Criterion
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ICML
2003
IEEE
14 years 8 months ago
Hidden Markov Support Vector Machines
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
TRECVID
2007
13 years 9 months ago
Experimenting VIREO-374: Bag-of-Visual-Words and Visual-Based Ontology for Semantic Video Indexing and search
In this paper, we present our approaches and results of high-level feature extraction and automatic video search in TRECVID-2007. In high-level feature extraction, our main focus ...
Chong-Wah Ngo, Yu-Gang Jiang, Xiao-Yong Wei, Feng ...
ICPR
2006
IEEE
14 years 9 months ago
Stroke Segmentation of Chinese Characters Using Markov Random Fields
This paper presents Markov random fields (MRFs) to segment strokes of Chinese characters. The distortions caused by the thinning process make the thinning-based stroke segmentatio...
Jia Zeng, Zhi-Qiang Liu
TRECVID
2008
13 years 9 months ago
National Institute of Informatics, Japan at TRECVID 2008
This paper reports our experiments for TRECVID 2008 tasks: high level feature extraction, search and contentbased copy detection. For the high level feature extraction task, we use...
Duy-Dinh Le, Xiaomeng Wu, Shin'ichi Satoh, Sheetal...
JCB
2008
159views more  JCB 2008»
13 years 8 months ago
BayesMD: Flexible Biological Modeling for Motif Discovery
We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
Man-Hung Eric Tang, Anders Krogh, Ole Winther