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The neocognitron is a hierarchical, multilayered
artificial neural network
In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a computational model inspired by the structure and functions of biological neural networks.
A neural network consists of connected ...
proposed by
Kunihiko Fukushima in 1979.
It has been used for Japanese
handwritten character recognition and other
pattern recognition
Pattern recognition is the task of assigning a class to an observation based on patterns extracted from data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess PR capabilities but their p ...
tasks, and served as the inspiration for
convolutional neural network
A convolutional neural network (CNN) is a type of feedforward neural network that learns features via filter (or kernel) optimization. This type of deep learning network has been applied to process and make predictions from many different ty ...
s.
Previously in 1969, he published a similar architecture, but with hand-designed kernels inspired by convolutions in mammalian vision. In 1975 he improved it to the Cognitron, and in 1979 he improved it to the neocognitron, which ''learns'' all convolutional kernels by
unsupervised learning
Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data. Other frameworks in the spectrum of supervisions include weak- or semi-supervision, wh ...
(in his terminology, "
self-organized by 'learning without a teacher'").
The neocognitron was inspired by the model proposed by
Hubel &
Wiesel in 1959. They found two types of cells in the visual primary cortex called ''
simple cell'' and ''
complex cell'', and also proposed a cascading model of these two types of cells for use in pattern recognition tasks.
The neocognitron is a natural extension of these cascading models. The neocognitron consists of multiple types of cells, the most important of which are called ''S-cells'' and ''C-cells.'' The local features are extracted by S-cells, and these features' deformation, such as local shifts, are tolerated by C-cells. Local features in the input are integrated gradually and classified in the higher layers. The idea of local feature integration is found in several other models, such as the ''
Convolutional Neural Network
A convolutional neural network (CNN) is a type of feedforward neural network that learns features via filter (or kernel) optimization. This type of deep learning network has been applied to process and make predictions from many different ty ...
'' model, the ''
SIFT'' method, and the ''
HoG'' method.
There are various kinds of neocognitron. For example, some types of neocognitron can detect multiple patterns in the same input by using backward signals to achieve
selective attention.
See also
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Artificial neural network
In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a computational model inspired by the structure and functions of biological neural networks.
A neural network consists of connected ...
*
Deep learning
Deep learning is a subset of machine learning that focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience a ...
*
Pattern recognition
Pattern recognition is the task of assigning a class to an observation based on patterns extracted from data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess PR capabilities but their p ...
*
Receptive field
The receptive field, or sensory space, is a delimited medium where some physiological stimuli can evoke a sensory neuronal response in specific organisms.
Complexity of the receptive field ranges from the unidimensional chemical structure of od ...
*
Self-organizing map
*
Unsupervised learning
Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data. Other frameworks in the spectrum of supervisions include weak- or semi-supervision, wh ...
Notes
References
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External links
Neocognitronon
Scholarpedia
''Scholarpedia'' is an English-language wiki-based online encyclopedia with features commonly associated with Open access (publishing), open-access online academic journals, which aims to have quality content in science and medicine.
''Scholarpe ...
NeoCognitron by Ing. Gabriel Minarik- application (C#) and video
Neocognitron resources at Visiome Platform- includes MATLAB environment
Beholder- a Neocognitron simulator
Artificial neural networks
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