BUIDLING ORNAMENTAL FISH SHOP MANAGEMENT WEBSITE

Abstract

This thesis presents the development of a system for managing an aquarium shop, incorporating an advanced product search system based on image recognition using deep learning. The system leverages convolutional neural networks (CNNs) to analyze and classify images of aquarium products, allowing users to find specific items by simply uploading images. The system provides an intuitive user interface for both customers and shop administrators, enabling efficient inventory management, product categorization, and real-time updates. The integration of deep learning technologies enhances the accuracy and efficiency of product searches, offering a modern solution to optimize the shopping experience. This platform aims to streamline operations, improve customer satisfaction, and elevate the overall user experience in the aquarium retail sector.