Image Classification using modified Convolutional Neural Network

Abstract

Image classification is the field of research since decades. With evaluation of new technologies, the performance of image classification has been improved and this is evident by it’s us in routine life. However there are scopes to use the deep learning networks to further improve the complex image classification problems. In this paper, the Convolution neural network based(CNN) image classification is evaluated by changing the parameters of CNN like number of layers, number of neurons, block size of convolution operation etc. The parametric analysis in terms of accuracy number of iteration for convergence is illustrated in result section. The standard dataset of Intel image classification is used for evaluation of performance. The maximum accuracy has been achieved.