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» Data Reduction Using Multiple Models Integration
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ICCV
2009
IEEE
16 years 7 months ago
Robust Fitting of Multiple Structures: The Statistical Learning Approach
We propose an unconventional but highly effective approach to robust fitting of multiple structures by using statistical learning concepts. We design a novel Mercer kernel for t...
Tat-Jun Chin, Hanzi Wang, David Suter
IROS
2006
IEEE
136views Robotics» more  IROS 2006»
15 years 8 months ago
Adaptive Interacting Multiple Models applied on pedestrian tracking in car parks
— To address perception problems we must be able to track dynamics targets of the environment. An important issue of tracking is filtering problem in which estimates of the targ...
Julien Burlet, Olivier Aycard, Anne Spalanzani, Ch...
TIT
2008
141views more  TIT 2008»
15 years 2 months ago
Dimensionality Reduction for Distributed Estimation in the Infinite Dimensional Regime
Distributed estimation of an unknown signal is a common task in sensor networks. The scenario usually envisioned consists of several nodes, each making an observation correlated wi...
Olivier Roy, Martin Vetterli
120
Voted
ICC
2007
IEEE
126views Communications» more  ICC 2007»
15 years 8 months ago
Modeling and Analysis of Handoffs in Cellular and WLAN Integration
—In this paper, we propose an integrated service-based handoff scheme with (ISBQ) and without queue capability (ISB) for the cellular and WLAN integration. The proposed handoff s...
Weiwei Xia, Lianfeng Shen
TASLP
2002
84views more  TASLP 2002»
15 years 2 months ago
Maximum likelihood multiple subspace projections for hidden Markov models
The first stage in many pattern recognition tasks is to generate a good set of features from the observed data. Usually, only a single feature space is used. However, in some compl...
Mark J. F. Gales