Automated Product Categorization in E-commerce: An Image Processing and ML Approach

Abstract- E-commerce is undergoing a rapid expansion, which has led to the emergence of many better product categorization techniques that help in improving the searchability, reducing manual effort, and improving the user’s search. The purpose of this paper is to discuss the techniques of image recognition, such as Convolutional Neural Networks (CNNs), EfficientNet, and Vision Transformers (ViTs), in order to improve the product categorization in e-commerce. In this context, the research paper is going to discuss the implementation of deep learning models, in order to categorize the product images automatically. The research paper is going to discuss how these models work, what challenges researchers had to face, what are the future directions for the research, and what are the limitations of the research. The purpose of this paper is to provide a comprehensive study on implementing machine learning models to categorize the products, and it is expected to be useful for e-commerce platforms. This is going to enhance shopping, and it will be a great benefit for the customers.