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Titlebook: Artificial Neural Networks - ICANN 2010; 20th International C Konstantinos Diamantaras,Wlodek Duch,Lazaros S. Il Conference proceedings 201

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樓主: Reagan
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發(fā)表于 2025-3-25 06:32:02 | 只看該作者
22#
發(fā)表于 2025-3-25 09:44:44 | 只看該作者
Manufacturing and Mechanical Propertiesorithm. A smoothing term is included that penalizes the complexity of the family of distances and avoids overfitting..The experimental results suggest that the method proposed outperforms a standard metric learning algorithm and improves classification and clustering results based on a single dissim
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發(fā)表于 2025-3-25 13:57:28 | 只看該作者
0302-9743 sist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation funct978-3-642-15824-7978-3-642-15825-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
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發(fā)表于 2025-3-25 19:27:29 | 只看該作者
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發(fā)表于 2025-3-25 22:10:48 | 只看該作者
Applications of Communications Theorye defined empirically and the optimization of parameters has been known as a remaining problem of PCNN. In this study, we show a method to apply the real coded genetic algorithm to the parameter optimization of the PCNN and we also show performances of pattern recognition by the PCNN with learned parameters.
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發(fā)表于 2025-3-26 02:13:39 | 只看該作者
27#
發(fā)表于 2025-3-26 05:01:46 | 只看該作者
Konstantinos Diamantaras,Wlodek Duch,Lazaros S. IlFast track conference proceeding.Unique visibility.State-of-the-art research
28#
發(fā)表于 2025-3-26 08:42:43 | 只看該作者
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發(fā)表于 2025-3-26 13:57:08 | 只看該作者
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