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» The Bias Problem and Language Models in Adaptive Filtering
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CVPR
2010
IEEE
12 years 6 months ago
Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling
Robust tracking of abrupt motion is a challenging task in computer vision due to the large motion uncertainty. In this paper, we propose a stochastic approximation Monte Carlo (...
Xiuzhuang Zhou and Yao Lu
IEICET
2008
136views more  IEICET 2008»
13 years 9 months ago
Bilingual Cluster Based Models for Statistical Machine Translation
We propose a domain specific model for statistical machine translation. It is wellknown that domain specific language models perform well in automatic speech recognition. We show ...
Hirofumi Yamamoto, Eiichiro Sumita
ESANN
2001
13 years 10 months ago
A divide-and-conquer learning architecture for predicting unknown motion
Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisti...
Patrice Wira, Jean-Philippe Urban, Julien Gresser
BMVC
2010
13 years 7 months ago
On-line Adaption of Class-specific Codebooks for Instance Tracking
Off-line trained class-specific object detectors are designed to detect any instance of the class in a given image or video sequence. In the context of object tracking, however, o...
Juergen Gall, Nima Razavi, Luc J. Van Gool
IJCNLP
2005
Springer
14 years 2 months ago
Inversion Transduction Grammar Constraints for Mining Parallel Sentences from Quasi-Comparable Corpora
Abstract. We present a new implication of Wu’s (1997) Inversion Transduction Grammar (ITG) Hypothesis, on the problem of retrieving truly parallel sentence translations from larg...
Dekai Wu, Pascale Fung