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» Gaussian Process Models of Spatial Aggregation Algorithms
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ICRA
2010
IEEE
145views Robotics» more  ICRA 2010»
13 years 6 months ago
Modeling and decision making in spatio-temporal processes for environmental surveillance
Abstract— The need for efficient monitoring of spatiotemporal dynamics in large environmental surveillance applications motivates the use of robotic sensors to achieve sufficie...
Amarjeet Singh 0003, Fabio Ramos, Hugh D. Whyte, W...
CAIP
2007
Springer
217views Image Analysis» more  CAIP 2007»
14 years 1 months ago
Mixture Models Based Background Subtraction for Video Surveillance Applications
— Background subtraction is a method commonly used to segment objects of interest in image sequences. By comparing new frames to a background model, regions of interest can be fo...
Chris Poppe, Gaëtan Martens, Peter Lambert, R...
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
13 years 2 months ago
Aggregation-based model reduction of a Hidden Markov Model
This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
Kun Deng, Prashant G. Mehta, Sean P. Meyn
DAC
2006
ACM
14 years 8 months ago
Statistical timing analysis with correlated non-gaussian parameters using independent component analysis
We propose a scalable and efficient parameterized block-based statistical static timing analysis algorithm incorporating both Gaussian and non-Gaussian parameter distributions, ca...
Jaskirat Singh, Sachin S. Sapatnekar
BMCBI
2004
208views more  BMCBI 2004»
13 years 7 months ago
Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
Vadim Alexandrov, Mark Gerstein