Image noise types recognition using convolutional neural network with principal components analysis

2017 ◽  
Vol 11 (12) ◽  
pp. 1238-1245 ◽  
Author(s):  
Hui Ying Khaw ◽  
Foo Chong Soon ◽  
Joon Huang Chuah ◽  
Chee-Onn Chow
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Image Noise ◽  
Components Analysis

A Principal Components Analysis Self-Organizing Neural Network Model and Computational Experiment

2013 ◽  
Vol 756-759 ◽  
pp. 3330-3335
Author(s):  
Ji Fu Nong
Keyword(s):  
Neural Network ◽  
Principal Components Analysis ◽  
Network Model ◽  
Neural Network Model ◽  
Principal Components ◽  
Computational Experiment ◽  
Neural Model ◽  
Self Organizing Map ◽  
Components Analysis ◽  
Self Organizing

We propose a new self-organizing neural model that performs principal components analysis. It is also related to the adaptive subspace self-organizing map (ASSOM) network, but its training equations are simpler. Experimental results are reported, which show that the new model has better performance than the ASSOM network.

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