Refereed full papers (journals, book chapters, international conferences)

1980

@article{Fuk1980,
	vgclass =	{refpap},
	vgproject =	{nn,invariance},
	author =	{Kunihiko Fukushima},
	title =	{{N}eocognitron: A Self-organizing Neural Network Model for
	a Mechanism of Pattern Recognition Unaffected by Shift in Position},
	journal =	{Biological Cybernetics},
	volume =	{36},
	pages =	{193--202},
	year =	{1980},
	abstract =	{A neural network model for a mechanism of visual pattern
	recognition is proposed in this paper. The network is self-organizing
	by ``learning without a teacher'', and acquires an ability to recognize
	stimulus patterns based on the geometrical similarity (Gestalt) of
	their shapes without affected by their positions. This network is given
	a nickname ``neocognitron''. After completion of self-organization, the
	network has a structure similar to the hierarchy model of the visual
	nervous system proposed by Hubel and Wiesel. The network consists of an
	input layer (photoreceptor array) followed by a cascade connection of a
	number of modular structures, each of which is composed of two layers
	of cells connected in cascade. The first layer of each module consists
	of ``S-cells'', which show characteristics similar to simple cells or
	lower order hypercomplex cells, and the second layer consists of
	``C-cells'' similar to complex cells or higher order hypercomplex
	cells. The afferent synapses to each S-cell have plasticity and are
	modifiable. The network has an ability of unsupervised learning: We do
	not need any ``teacher'' during the process of self-organization, and
	it is only needed to present a set of stimulus patterns repeatedly to
	the input layer of the network.  The network has been simulated on a
	digital computer. After repetitive presentation of a set of stimulus
	patterns, each stimulus pattern has become to elicit an output only
	from one of the C-cells of the last layer, and conversely, this C-cell
	has become selectively responsive only to that stimulus pattern. That
	is, none of the C-cells of the last layer responds to more than one
	stimulus pattern. The response of the C-cells of the last layer is not
	affected by the pattern's position at all. Neither is it affected by a
	small change in shape nor in size of the stimulus pattern.},
}