Change Detection using Pulse Coupled Neural Network
Geeta Desai and Sonal Gahankari. Article: Change Detection using Pulse Coupled Neural Network. IJCA Proceedings on National Conference on Growth of Technologies in Electronics, Telecom and Computers - India's Perception GTETC-IP:1-4, May 2014. Full text available. BibTeX
@article{key:article,
author = {Geeta Desai and Sonal Gahankari},
title = {Article: Change Detection using Pulse Coupled Neural Network},
journal = {IJCA Proceedings on National Conference on Growth of Technologies in Electronics, Telecom and Computers - India's Perception},
year = {2014},
volume = {GTETC-IP},
pages = {1-4},
month = {May},
note = {Full text available}
}
Abstract
In this paper a context sensitive technique for unsupervised change detection in multitemporal images using Pulse coupled neural network is proposed . PCNN is an biologically inspired neural network based on cats visual cortical neurons. The key strength of PCNN model is that it can operate without training and in comparison with more traditional Neural network s it has benefits like signal associated to the PCNN has properties of invariance to changes in rotation ,scale ,translation of an input patterns . This property is very useful when dealing with very high resolution images.
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