Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position

  title={Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position},
  author={Kunihiko Fukushima},
  journal={Biological Cybernetics},
  • K. Fukushima
  • Published 1 April 1980
  • Computer Science, Biology
  • Biological Cybernetics
A neural network model for a mechanism of visual pattern recognition is proposed in this paper. [] Key Result Neither is it affected by a small change in shape nor in size of the stimulus pattern.

Artificial vision by multi-layered neural networks: Neocognitron and its advances

Analysis of Multi-Layer Neural Network’s Recognition Mechanism Using Alopex Algorithm

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Self-Organizing Formation of Receptive Fields and Competitive Systems

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Multiwinner feedforward self-organizing neural network with a distributed representation of information

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A model of complex cell development by information separation

It is demonstrated that neurons in layer C learn invariance to shift in input position, which explains complex cell development in terms of the principle of information separation.

A Generalized Net Model of the Neocognitron Neural Network

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Hierarchical Models of the Visual System

  • Thomas Serre
  • Computer Science
    Encyclopedia of Computational Neuroscience
  • 2014
Deep convolutional networks are architecturally similar neural networks that have led to impressive results in a wide range of engineering disciplines, from computer vision to natural language processing, and artificial intelligence more broadly.

On the self-organization of a hierarchical memory for compositional object representation in the visual cortex

A functional model of a self-organizing hierarchical memory network based on hypothetical neuronal mechanisms involved in cortical processing and adaptation is proposed, showing its ability to recognize identity and gender of the persons from alternative face views not shown before.



Cognitron: A self-organizing multilayered neural network

  • K. Fukushima
  • Computer Science, Biology
    Biological Cybernetics
  • 2004
A new hypothesis for the organization of synapses between neurons is proposed: “The synapse from neuron x to neuron y is reinforced when x fires provided that no neuron in the vicinity of y is firing stronger than y”, and a new algorithm with which a multilayered neural network is effectively organized can be deduced.

Receptive fields, binocular interaction and functional architecture in the cat's visual cortex

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Visual properties of neurons in inferotemporal cortex of the Macaque.

There are several lines of evidence suggesting that a possible site for further processing of visual information and perhaps even for storage of such information might, in the monkey, be inferotemporal cortexthe cortex on the inferior convexity of the temporal lobe.

Ferrier lecture - Functional architecture of macaque monkey visual cortex

  • D. HubelT. Wiesel
  • Biology
    Proceedings of the Royal Society of London. Series B. Biological Sciences
  • 1977
In most respects the above description fits the newborn monkey just as well as the adult, suggesting that area 17 is largely genetically programmed.

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By four independent anatomical methods it has been shown that these columns have an ocular dominance column all cells respond preferentially to the same eye, in that cells with common physiological properties are grouped together in vertically organized systems of columns.


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Feature Extraction and Recognition of Handwritten Characters by Homogeneous Layers

It is not necessary that an artificial recognition system is constructed in the same way as neuronal systems; but if it is based on the same principles of perception — as far as they are known — it might have a better chance of performing the same recognition operation.

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It is your own time to continue reading habit and one of the books you can enjoy now is a proposed model for visual information processing in the human brain here.

Self-Organization of a Neural Network which Gives Position-Invariant Response

A new algorithm for self-organizing a multilayered neural network which has an ability to recognize patterns based on the geometrical similarity of their shapes, whose nickname is "neo-cognitron", has a structure similar to the hierarchy model of the visual nervous system proposed by Hubel and Wiesel.