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TASLP
2010
138views more  TASLP 2010»
13 years 3 months ago
Glimpsing IVA: A Framework for Overcomplete/Complete/Undercomplete Convolutive Source Separation
Abstract--Independent vector analysis (IVA) is a method for separating convolutedly mixed signals that significantly reduces the occurrence of the well-known permutation problem in...
Alireza Masnadi-Shirazi, Wenyi Zhang, Bhaskar D. R...
ECCV
2006
Springer
14 years 9 days ago
Learning Semantic Scene Models by Trajectory Analysis
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...
Xiaogang Wang, Kinh Tieu, Eric Grimson
POPL
2005
ACM
14 years 9 months ago
Precise interprocedural analysis using random interpretation
We describe a unified framework for random interpretation that generalizes previous randomized intraprocedural analyses, and also extends naturally to efficient interprocedural an...
Sumit Gulwani, George C. Necula
ICASSP
2008
IEEE
14 years 3 months ago
Unsupervised optimal phoneme segmentation: Objectives, algorithm and comparisons
Phoneme segmentation is a fundamental problem in many speech recognition and synthesis studies. Unsupervised phoneme segmentation assumes no knowledge on linguistic contents and a...
Yu Qiao, Naoya Shimomura, Nobuaki Minematsu
ECCV
2008
Springer
14 years 10 months ago
Robust Visual Tracking Based on an Effective Appearance Model
Most existing appearance models for visual tracking usually construct a pixel-based representation of object appearance so that they are incapable of fully capturing both global an...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang