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» Analysing Randomized Distributed Algorithms
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CVPR
2004
IEEE
16 years 4 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
CISS
2008
IEEE
15 years 8 months ago
Near optimal lossy source coding and compression-based denoising via Markov chain Monte Carlo
— We propose an implementable new universal lossy source coding algorithm. The new algorithm utilizes two wellknown tools from statistical physics and computer science: Gibbs sam...
Shirin Jalali, Tsachy Weissman
ICMCS
2006
IEEE
107views Multimedia» more  ICMCS 2006»
15 years 8 months ago
Rain Removal in Video by Combining Temporal and Chromatic Properties
Removal of rain streaks in video is a challenging problem due to the random spatial distribution and fast motion of rain. This paper presents a new rain removal algorithm that inc...
Xiaopeng Zhang, Hao Li, Yingyi Qi, Wee Kheng Leow,...
NIPS
2003
15 years 3 months ago
Self-calibrating Probability Forecasting
In the problem of probability forecasting the learner’s goal is to output, given a training set and a new object, a suitable probability measure on the possible values of the ne...
Vladimir Vovk, Glenn Shafer, Ilia Nouretdinov
151
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ICIP
2007
IEEE
15 years 2 months ago
Statistical Multiscale Image Segmentation via Alpha-Stable Modeling
This paper presents a new statistical image segmentation algorithm, in which the texture features are modeled by Symmetric Alpha-Stable (SαS) distributions. These features are ef...
Tao Wan, Cedric Nishan Canagarajah, Alin Achim