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» Feature selection with neural networks
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GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
15 years 2 months ago
Reinforcement learning for games: failures and successes
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
Wolfgang Konen, Thomas Bartz-Beielstein
ICANN
1997
Springer
15 years 2 months ago
A Feature Map Approach to Pose Estimation Based on Quaternions
This paper proposes a novel solution to the problem of pose estimation of three-dimensional objects using feature maps. Our approach relies on quaternions as the mathematical repre...
S. Winkler, Patrick Wunsch, Gerd Hirzinger
ESANN
2004
14 years 11 months ago
Visual person tracking with a Supervised Conditioning-SOM
The classification problem of determining if a surveillance camera sees persons is tackled with two neural models: the Self-Organizing Map (SOM) with supervision as in a classical ...
J. David Buldain Pérez, José El&iacu...
PRL
1998
93views more  PRL 1998»
14 years 9 months ago
A connectionist method for pattern classification with diverse features
A novel connectionist method is proposed to simultaneously use diverse features in an optimal way for pattern classification. Unlike methods of combining multiple classifiers, a m...
Ke Chen 0001
ICDAR
2009
IEEE
14 years 7 months ago
Invariant Primitives for Handwritten Arabic Script: A Contrastive Study of Four Feature Sets
The choice of relevant features is very decisive in handwriting recognition rate. Our aim is to present some useful structural and statistical features and see their degree of var...
Sofiene Haboubi, Samia Maddouri, Noureddine Ellouz...