An Ai-Powered Visual Search For Electronic Device Products Via Mobile Shopping

Abstract

The creation of a state-of-the-art mobile application platform that accommodates a wide range of functions for its users is the thesis's capstone. An immersive electronic device experience is created by functionality that extends from the easy viewing and searching of products to the thorough completion of the purchase and payment processes. Using the Flutter framework and the Dart programming language, this application is carefully designed to function well on an Android emulator. The capacity to explore, search, and participate in the buying process is granted to users, who can do so by navigating through an intuitive interface that improves their overall contact with electronic devices. The dynamic elements integrated into the program facilitate the purchasing process and offer users a satisfying shopping experience. The thesis delves deeper into technological developments and presents a novel paradigm that sits beneath the mobile application system. Using Deep-CNN-powered object recognition, the model focuses on recognizing unique and distinguishing aspects in photographs, adding a new level of depth to the shopping experience. This model, which is focused on electronic devices, it helps to produce a more accurate and sophisticated representation of items in the application.