Image Categorization through Convolutional Neural Network

Abstract

Abstract: Ten years ago, there were barriers to ideal accuracy in many computer vision issues. But the emergence of deep learning techniques brought about a dramatic change that greatly improved the accuracy of these problems. Among these, image classification stands out as a key problem: it is the challenge of accurately classifying images into their corresponding classifications, such dogs and cats. This research aims to improve accuracy by utilizing state-of-the-art object detecting algorithms. In order to tackle this, a great deal of effort has gone into building a convolutional neural network (CNN) that is robust and designed with image categorization in mind. The principal goal is to leverage the capabilities of cutting-edge object identification techniques in order to achieve significant improvements in image classification accuracy.