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AIA
2006
13 years 8 months ago
Recurrent and Concurrent Neural Networks for Objects Recognition
A system based on a neural network framework is considered. We used two neural networks, an Elman network [1][2] and a Kohonen (concurrent) network [3], for a categorization task....
Federico Cecconi, Marco Campenní
AI
2002
Springer
13 years 7 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
WAPCV
2004
Springer
14 years 22 days ago
TarzaNN: A General Purpose Neural Network Simulator for Visual Attention Modeling
A number of computational models of visual attention exist, but making comparisons is difficult due to the incompatible implementations and levels at which the simulations are con...
Albert L. Rothenstein, Andrei Zaharescu, John K. T...
EWLR
1999
Springer
13 years 11 months ago
Toward Seamless Transfer from Simulated to Real Worlds: A Dynamically-Rearranging Neural Network Approach
In the field of evolutionary robotics artificial neural networks are often used to construct controllers for autonomous agents, because they have useful properties such as the ab...
Peter Eggenberger, Akio Ishiguro, Seiji Tokura, To...
IJON
2008
88views more  IJON 2008»
13 years 7 months ago
Neural network construction and training using grammatical evolution
The term neural network evolution usually refers to network topology evolution leaving the network's parameters to be trained using conventional algorithms. In this paper we ...
Ioannis G. Tsoulos, Dimitris Gavrilis, Euripidis G...