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ESANN
2003
15 years 7 months ago
Autonomous learning algorithm for fully connected recurrent networks
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre
ICANN
2003
Springer
15 years 11 months ago
Unsupervised Learning of a Kinematic Arm Model
Abstract. An abstract recurrent neural network trained by an unsupervised method is applied to the kinematic control of a robot arm. The network is a novel extension of the Neural ...
Heiko Hoffmann, Ralf Möller
MICCAI
2002
Springer
16 years 7 months ago
Comparative Exudate Classification Using Support Vector Machines and Neural Networks
After segmenting candidate exudates regions in colour retinal images we present and compare two methods for their classification. The Neural Network based approach performs margina...
Alireza Osareh, Majid Mirmehdi, Barry T. Thomas, R...
DL
1999
Springer
154views Digital Library» more  DL 1999»
15 years 10 months ago
SOMLib: A Digital Library System Based on Neural Networks
Digital Libraries have gained tremendous interest with numerous research projects addressing the wealth of challenges in this field. While computational intelligence systems are ...
Andreas Rauber, Dieter Merkl
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
16 years 20 days ago
Generating large-scale neural networks through discovering geometric regularities
Connectivity patterns in biological brains exhibit many repeating motifs. This repetition mirrors inherent geometric regularities in the physical world. For example, stimuli that ...
Jason Gauci, Kenneth O. Stanley