A Method to Solve overflow or underflow errors Resulting from Activation functions in Convolutional Neural Networks

In this paper, a method is proposed to correct overflow errors of resulting values that can occur when the cross-entropy loss function is used as a softmax and ReLU as an activation function of the convolutional neural network. Since conventional softmax and cross-entropy functions include exponenti...

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Veröffentlicht in:	International Information Institute (Tokyo). Information Jg. 20; H. 11; S. 8151 - 8158
Hauptverfasser:	Jeong, JunMo, Choi, SeJin, Kim, ChiYong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Koganei International Information Institute 01.11.2017
Schlagworte:	Activation Algorithms Artificial neural networks Classification Divergence Entropy Error correction Methods Neural networks Neurons
ISSN:	1343-4500, 1344-8994
Online-Zugang:	Volltext
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