Journal ArticleDOI
Classification of patterns using a self-organizing neural network
TLDR
Results for expanded neocognitron architectures operating on complex images of 128 × 128 pixels are described, giving insight into the role of various model parameters and their proper values, as well as demonstrating the model's applicability to complex images.About:
This article is published in Neural Networks.The article was published on 1988-01-01. It has received 40 citations till now. The article focuses on the topics: Neocognitron & Artificial neural network.read more
Citations
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Journal ArticleDOI
Neural networks: algorithms, applications, and programming techniques
TL;DR: The authors survey the most common neural-network architectures and show how neural networks can be used to solve actual scientific and engineering problems and describe methodologies for simulating neural- network architectures on traditional digital computing systems.
Journal ArticleDOI
Artificial convolution neural network techniques and applications for lung nodule detection
Shih-Chung Benedict Lo,S.-L.A. Lou,Jyh-Shyan Lin,Matthew T. Freedman,M.V. Chien,Seong Ki Mun +5 more
TL;DR: A double-matching method and an artificial visual neural network technique for lung nodule detection that modeled radiologists' reading procedures in order to instruct the artificial neural network to recognize the image patterns predefined and those of interest to experts in radiology.
Journal ArticleDOI
Neocognitron for handwritten digit recognition
TL;DR: This paper proposes an improved version of the neocognitron and tests its ability using a large database of handwritten digits (ETL1) to improve the recognition rate and removes accessory circuits that were appended to the previous versions.
Journal ArticleDOI
Cueing, feature discovery, and one-class learning for synthetic aperture radar automatic target recognition
TL;DR: A modular multi-stage architecture for focus-of-attention cueing, feature discovery and extraction, and one-class pattern learning and identification in synthetic aperture radar imagery is described.
Journal ArticleDOI
Classifier and shift-invariant automatic target recognition neural networks
TL;DR: A new feature space trajectory classifier neural network is described that identifies the class and pose of each object, rejects clutter false alarms, and overcomes various issues associated with other classier neural networks.
References
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Journal ArticleDOI
Neocognitron: A Self Organizing Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position
TL;DR: A neural network model for a mechanism of visual pattern recognition that is self-organized by “learning without a teacher”, and acquires an ability to recognize stimulus patterns based on the geometrical similarity of their shapes without affected by their positions.
Journal ArticleDOI
Neocognitron: A neural network model for a mechanism of visual pattern recognition
TL;DR: In this article, a large-scale network with a learning-with-a-teacher (L2Teacher) process is used for reinforcement of the modifiable synapses in the new large-size model, instead of the learning-without-a teacher process applied to a previous model.
Proceedings ArticleDOI
Pattern Recognition With A Neural Net
TL;DR: The neocognitron architecture is described and the basis of its operation for both the learning and recognition modes is explained.
Related Papers (5)
Neocognitron: A new algorithm for pattern recognition tolerant of deformations and shifts in position
Kunihiko Fukushima,Sei Miyake +1 more