Titlebook: Artificial Neural Networks in Pattern Recognition; 7th IAPR TC3 Worksho Friedhelm Schwenker,Hazem M. Abbas,Edmondo Trentin Conference proce

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书目名称Artificial Neural Networks in Pattern Recognition影响因子(影响力)




书目名称Artificial Neural Networks in Pattern Recognition影响因子(影响力)学科排名




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书目名称Artificial Neural Networks in Pattern Recognition网络公开度学科排名




书目名称Artificial Neural Networks in Pattern Recognition被引频次




书目名称Artificial Neural Networks in Pattern Recognition被引频次学科排名




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书目名称Artificial Neural Networks in Pattern Recognition年度引用学科排名




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书目名称Artificial Neural Networks in Pattern Recognition读者反馈学科排名

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,Die Gynäkologie des Truppenarztes,ty of the problem to face, linear dynamical systems may directly contribute to provide a good solution at a reduced computational cost, or indirectly provide support at a pre-training stage for nonlinear models. We present and discuss several approaches, both linear and nonlinear, where linear dynam

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https://doi.org/10.1007/978-3-662-34565-8e usually inferior to support vector machines (SVMs). To improve the generalization abilities of MAMCs, in this paper, we propose optimizing slopes and bias terms of separating hyperplanes after the coefficient vectors of the hyperplanes are obtained. The bias term is optimized so that the number of

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