Research on mass image classification based on CNN deep learning

Abstract

Image classification is one of the most important fundamental problems in computer vision research. It involves many basic problems in the field of computer vision, such as feature extraction, object detection and so on. Therefore, the study of image classification is helpful to understand the basic knowledge in the field of computer vision. Since CNN model made a breakthrough, deep learning has been widely used in image classification field. This paper aims to apply the deep learning method to solve the problem of image classification, study and understand image classification problems to help further study and study in the future. By learning 50000 well classified images, this research tries to find the most suitable algorithm and model to achieve the optimal classification, realizing 20 classification and 100 classifications for 10000 unclassified images with the highest accuracy possible.