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	Fukushima, Kunihiko     Options: All Media Types Journals Proceedings Div Books Whole Books Other Date Reviewed Title Author Publisher Published Date Descending Ascending Date Reviewed     1 - 2 of 2 reviews       Neocognitron capable of incremental learning Fukushima K. Neural Networks 17(1): 37-46, 2004.  Type: Article The learning algorithms within neocognitron are discussed in this paper. Neocognitron is a neural network model that has two distinctive types of cells: S-cells and C-cells. The prime use of this type of neural network i...... Apr 22 2004     A Neural Network for Visual Pattern Recognition Fukushima K. Computer 21(3): 65-75, 1988.  Type: Article This paper proposes a neural network model that has the following properties and abilities: pattern recognition, selective attention, segmentation, and associative recall. This network of neuron-like analog cells has a hierarchical mul...... Aug 1 1989
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