E-Commerce Website with Virtual Trial Feature

E-Commerce Website with Virtual Trial Feature

Shubhangi Rahul Gaikwad, Komal Ashok Gawade, Abhishek Rajkumar Gupta, Pratik Gajanand Gupta, Ashwini Changdev Kadus

Department of Computer Engineering,

Jayawantrao Sawant College of

Engineering, Pune, India

Abstract:

In this paper, we describe the creation and deployment of an effective e-commerce website with state-of-the-art technologies to improve user experience and enable smooth transactions. Deep Neural Networks (DNN) are used by our platform to deliver individualized product recommendations based on the interests of each unique user. In addition, we incorporate computer vision technology to facilitate product classification, image recognition, and image-based search capabilities, making it simple for customers to locate related products. Flask, a lightweight Python framework, is used in the development of the web application to ensure effective processing of HTTP requests and dynamic content delivery. Additionally, we present a novel functionality that incorporates research papers associated with items, enabling users to get pertinent scholarly literature straight from the platform. Prioritization is also given to security measures, with user data being protected via encryption and secure authentication methods.

Keyword: Image processing, E-commerce, Virtual Trial, Computer Vision, Shopping, Deep Neural Network