Simple convolutional neural network on image classification

In recent years, deep learning has been used in image classification, object tracking, pose estimation, text detection and recognition, visual saliency detection, action recognition and scene labeling. Auto Encoder, sparse coding, Restricted Boltzmann Machine, Deep Belief Networks and Convolutional neural networks is commonly used models in deep learning. Among different type of models, Convolutional neural networks has been demonstrated high performance on image classification. In this paper we bulided a simple Convolutional neural network on image classification. This simple Convolutional neural network completed the image classification. Our experiments are based on benchmarking datasets minist [1] and cifar-10. On the basis of the Convolutional neural network, we also analyzed different methods of learning rate set and different optimization algorithm of solving the optimal parameters of the influence on image classification.