Reconfiguration of Spiking Neural Network for Optimization with Applications to Image Processing

This paper depicts the restructuring of different models of third generation of Artificial neural network, that is, the spiking neural networks for image processing applications. The proposed work aims towards implementation of a novel algorithm using different models of Spiking Neural Networks which will improve upon the optimization results in the field of image processing. In this paper, we focus on various evaluation parameters like mean square error, mean absolute error peak signal to noise ratios as well as enhance the output using ANN as wellas Leaky Integrate and firing Model of Spiking Neural Networks.