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» Person Tracking Based on a Hybrid Neural Probabilistic Model
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ICANN
2011
Springer
12 years 8 months ago
Person Tracking Based on a Hybrid Neural Probabilistic Model
This article presents a novel approach for a real-time person tracking system based on particle filters that use different visual streams. Due to the difficulty of detecting a pe...
Wenjie Yan, Cornelius Weber, Stefan Wermter
JAISE
2011
179views more  JAISE 2011»
12 years 7 months ago
A hybrid probabilistic neural model for person tracking based on a ceiling-mounted camera
Person tracking is an important topic in ambient living systems as well as in computer vision. In particular, detecting a person from a ceiling-mounted camera is a challenge since ...
Wenjie Yan, Cornelius Weber, Stefan Wermter
IJCNN
2008
IEEE
13 years 11 months ago
Hybrid learning architecture for unobtrusive infrared tracking support
—The system architecture presented in this paper is designed for helping an aged person to live longer independently in their own home by detecting unusual and potentially hazard...
K. K. Kiran Bhagat, Stefan Wermter, Kevin Burn
UAI
2000
13 years 6 months ago
Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach
The growth of Internet commerce has stimulated the use of collaborative filtering (CF) algorithms as recommender systems. Such systems leverage knowledge about the known preferenc...
David M. Pennock, Eric Horvitz, Steve Lawrence, C....
TNN
2008
177views more  TNN 2008»
13 years 4 months ago
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model
Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
Yoshua Bengio, Jean-Sébastien Senecal