A Fully Automated Pattern Classification Method of Combining Self-Organizing Map with Generalization Regression Neural Network

Neural Information Processing - Lecture Notes in Computer Science ◽

10.1007/11893257_15 ◽

2006 ◽

pp. 132-139 ◽

Cited By ~ 1

Author(s):

Chao-feng Li ◽

Jun-ben Zhang ◽

Zheng-you Wang ◽

Shi-tong Wang

Keyword(s):

Neural Network ◽

Pattern Classification ◽

Classification Method ◽

Self Organizing Map ◽

Self Organizing

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A Pattern Classification Method using Kernel Adaptive-Subspace Self-Organizing Map

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss.125.149 ◽

2005 ◽

Vol 125 (1) ◽

pp. 149-150 ◽

Cited By ~ 1

Author(s):

Hideaki Kawano ◽

Keiichi Horio ◽

Takeshi Yamakawa

Keyword(s):

Pattern Classification ◽

Classification Method ◽

Self Organizing Map ◽

Self Organizing

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Extended Self Organizing Map with Probabilistic Neural Network for Pattern Classification Problems

Advances in Intelligent Systems and Computing - Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014 ◽

10.1007/978-3-319-11933-5_19 ◽

2015 ◽

pp. 167-174

Author(s):

Prasenjit Dey ◽

Tandra Pal

Keyword(s):

Neural Network ◽

Pattern Classification ◽

Probabilistic Neural Network ◽

Self Organizing Map ◽

Classification Problems ◽

Extended Self ◽

Self Organizing

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Pile Samples Classification Method Based on the Self-Organizing Map Neural Network

Recent Advancement in Soil Behavior, in Situ Test Methods, Pile Foundations, and Tunneling ◽

10.1061/41044(351)27 ◽

2009 ◽

Author(s):

SiSi Liu ◽

MingHua Zhao ◽

MingHui Yang ◽

Wei Pan

Keyword(s):

Neural Network ◽

The Self ◽

Classification Method ◽

Self Organizing Map ◽

Self Organizing

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Classification of salt-contaminated velocities with self-organizing map neural network

The Leading Edge ◽

10.1190/1.1536131 ◽

2002 ◽

Vol 21 (12) ◽

pp. 1193-1196 ◽

Cited By ~ 3

Author(s):

Lin Zhang ◽

Al Fortier ◽

David C. Bartel

Keyword(s):

Neural Network ◽

Self Organizing Map ◽

Self Organizing

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Application of Self Organizing Map to Preprocessing Input Vectors for Convolutional Neural Network

Lecture Notes in Computer Science - Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning ◽

10.1007/978-3-030-30484-3_8 ◽

2019 ◽

pp. 96-100

Author(s):

Hiroshi Dozono ◽

Masafumi Tanaka

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Self Organizing Map ◽

Self Organizing

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The Suicide Attempt in an Artificial Neural Network (Self Organizing Map)

Journal of Neurology and Psychology ◽

10.13188/2332-3469.1000031 ◽

2016 ◽

Vol 4 (2) ◽

Cited By ~ 1

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Suicide Attempt ◽

Self Organizing Map ◽

Artificial Neural ◽

Self Organizing

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An extended Kalman filter using self-organizing map neural network

2008 Chinese Control and Decision Conference ◽

10.1109/ccdc.2008.4597551 ◽

2008 ◽

Author(s):

Dayuan Gao ◽

Hai Zhu ◽

Jianfeng Xu ◽

Dewen Hue

Keyword(s):

Neural Network ◽

Kalman Filter ◽

Extended Kalman Filter ◽

Self Organizing Map ◽

Self Organizing

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A Deep Clustering Algorithm Based on Self-organizing Map Neural Network

Intelligent Computing Methodologies - Lecture Notes in Computer Science ◽

10.1007/978-3-319-95957-3_20 ◽

2018 ◽

pp. 182-192

Author(s):

Yanling Tao ◽

Ying Li ◽

Xianghong Lin

Keyword(s):

Neural Network ◽

Clustering Algorithm ◽

Self Organizing Map ◽

Self Organizing

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Optimization of BOW Using Self Organizing Map Artificial Neural Network in Similar Images Retrieval Systems

Pattern Recognition and Image Analysis - Lecture Notes in Computer Science ◽

10.1007/978-3-642-38628-2_39 ◽

2013 ◽

pp. 330-339 ◽

Cited By ~ 1

Author(s):

Zied Elleuch ◽

Kirmene Marzouki

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Self Organizing Map ◽

Retrieval Systems ◽

Similar Images ◽

Artificial Neural ◽

Self Organizing

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Diagnosis of Breast Cancer Using Intelligent Information Systems Techniques

Nature-Inspired Computing ◽

10.4018/978-1-5225-0788-8.ch010 ◽

2016 ◽

pp. 203-214 ◽

Cited By ~ 1

Author(s):

Ahmad Al-Khasawneh

Keyword(s):

Breast Cancer ◽

Neural Network ◽

Cancer Diagnosis ◽

Multilayer Perceptron ◽

Breast Cancer Diagnosis ◽

Machine Learning Algorithms ◽

Data Sets ◽

Self Organizing Map ◽

Intelligent Information ◽

Self Organizing

Breast cancer is the second leading cause of cancer deaths in women worldwide. Early diagnosis of this illness can increase the chances of long-term survival of cancerous patients. To help in this aid, computerized breast cancer diagnosis systems are being developed. Machine learning algorithms and data mining techniques play a central role in the diagnosis. This paper describes neural network based approaches to breast cancer diagnosis. The aim of this research is to investigate and compare the performance of supervised and unsupervised neural networks in diagnosing breast cancer. A multilayer perceptron has been implemented as a supervised neural network and a self-organizing map as an unsupervised one. Both models were simulated using a variety of parameters and tested using several combinations of those parameters in independent experiments. It was concluded that the multilayer perceptron neural network outperforms Kohonen's self-organizing maps in diagnosing breast cancer even with small data sets.

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