Art

J-GLOBAL ID：201702250562619626   Reference number：17A1224452

A Convolutional Neural Network with Incremental Learning

インクリメンタル学習を用いた畳み込みニューラルネットワーク

Author (3)： Tomimori Haruka (Graduate School of Information, Production and Systems, Waseda University) ,  Chen Kui-Ting (Research Center of Information, Production and Systems, Waseda University) ,  Baba Takaaki (Graduate School of Information, Production and Systems, Waseda University)
Material： Journal of Signal Processing (Web)  (信号処理(Web))
Volume： 21  Issue： 4  Page： 155-158(J-STAGE)  Publication year： 2017 
JST Material Number： U0425A  ISSN： 1880-1013  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： ENGLISH (EN)

Thesaurus term： *neural network (biomodel) ,  *CAL ,  image recognition ,  speech recognition ,  method ,  extraction ,  accuracy ,  *Learning ,  *convolutional neuralnetwork
Semi thesaurus term： *incremental learning ,  method of learning ,  automated extraction ,  Recognition Accuracy

JST classification (2)： Artificial intelligence  (JE08000Z) ,  Neurocomputers  (JC06010Q)

Reference (7)：

• [1] K. Fukushima: Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position, Biological Cybernetics, Vol. 36, No. 4, pp. 193-202, 1980.
• [2] K. Fukushima and S. Miyake: Neocognitron: A new algorithm for pattern recognition tolerant of deformations and shifts in position, Pattern Recognition, Vol. 15, No. 6, pp. 455-469, 1982.
• [3] K. Fukushima: Neocognitron, A hierarchical neural network capable of visual pattern recognition, Neural Networks, Vol. 1, No. 2, pp. 119-130, 1988.
• [4] Y. LeCun, L. Bottou, Y. Bengio and P. Haffner: Gradient-based learning applied to document recognition, Proc. IEEE, Vol. 86, No. 11, pp. 2278-2324, 1998.
• [5] V. I. Arnold: Hierarchical neural networks for image interpretation, Lecture Notes in Computer Science, Vol. 2766, Springer, 2003.

Terms in the title (2)： インクリメンタル学習 ,  畳み込みニューラルネットワーク