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» Extracting Propositions from Trained Neural Networks
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IJCNN
2006
IEEE
15 years 3 months ago
Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...
ICANN
2005
Springer
15 years 3 months ago
A Neural Network Model for Inter-problem Adaptive Online Time Allocation
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
Matteo Gagliolo, Jürgen Schmidhuber
ICAISC
2004
Springer
15 years 3 months ago
Visualization of Hidden Node Activity in Neural Networks: I. Visualization Methods
Abstract. Quality of neural network mappings may be evaluated by visual inspection of hidden and output node activities for the training dataset. This paper discusses how to visual...
Wlodzislaw Duch
FGR
2000
IEEE
161views Biometrics» more  FGR 2000»
15 years 2 months ago
Learning and Synthesizing Human Body Motion and Posture
A novel approach is presented for estimating human body posture and motion from a video sequence. Human pose is defined as the instantaneous image plane configuration of a singl...
Rómer Rosales, Stan Sclaroff
TNN
2008
114views more  TNN 2008»
14 years 9 months ago
Relevance-Based Feature Extraction for Hyperspectral Images
Abstract--Hyperspectral imagery affords researchers all discriminating details needed for fine delineation of many material classes. This delineation is essential for scientific re...
Michael J. Mendenhall, Erzsébet Meré...