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CVPR
1999
IEEE
16 years 1 months ago
1999
IEEE
This paper presents a framework for integrating multiple sensory data, sparse range data and dense depth maps from shape from shading in order to improve the 3D reconstruction of ...
IJON
2008
14 years 11 months ago
2008
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 ...
GECCO
2005
Springer
15 years 5 months ago
2005
Springer
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
ISNN
2010
Springer
14 years 10 months ago
2010
Springer
As practical pattern classification tasks are often very-large scale and serious imbalance such as patent classification, using traditional pattern classification techniques in ...
GECCO
2007
Springer
15 years 3 months ago
2007
Springer
A primary goal of evolutionary robotics is to create systems that are as robust and adaptive as the human body. Moving toward this goal often involves training control systems tha...