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214
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CVPR
2010
IEEE
13 years 11 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
131
Voted
IJCNN
2008
IEEE
15 years 9 months ago
Biologically realizable reward-modulated hebbian training for spiking neural networks
— Spiking neural networks have been shown capable of simulating sigmoidal artificial neural networks providing promising evidence that they too are universal function approximat...
Silvia Ferrari, Bhavesh Mehta, Gianluca Di Muro, A...
JMLR
2006
125views more  JMLR 2006»
15 years 2 months ago
Spam Filtering Using Statistical Data Compression Models
Spam filtering poses a special problem in text categorization, of which the defining characteristic is that filters face an active adversary, which constantly attempts to evade fi...
Andrej Bratko, Gordon V. Cormack, Bogdan Filipic, ...
148
Voted
CVPR
2011
IEEE
14 years 6 months ago
Robust Tracking Using Local Sparse Appearance Model and K-Selection
Online learned tracking is widely used for it’s adaptive ability to handle appearance changes. However, it introduces potential drifting problems due to the accumulation of erro...
Baiyang Liu, junzhou Huang, Casimir Kulikowski, Li...
109
Voted
ICASSP
2008
IEEE
15 years 9 months ago
Sigma-delta resolution enhancement for far-field acoustic source separation
Many source separation algorithms fail to deliver robust performance when applied to signals recorded using highdensity microphone arrays where distance between sensor elements is...
Amin Fazel, Shantanu Chakrabartty