Year: 2025
Type: article
Abstract: In the rapidly evolving e-commerce industry, fashion classification and object detection play pivotal roles in enhancing user experience and improving operational efficiency. "Click & Cart" is an advanced system designed to address challenges in fashion retail by combining state-of-the-art computer vision techniques for object detection with machine learning algorithms for fashion classification. The system leverages deep learning models, particularly Convolutional Neural Networks (CNNs), to classify and detect fashion items such as clothing, accessories, and footwear from product images. Additionally, it uses object detection algorithms like YOLO (You Only Look Once) and Faster R-CNN to pinpoint key components within images, enabling the extraction of detailed information such as color, fabric, and style. By integrating both classification and detection, Click & Cart offers personalized recommendations, assists in virtual try-ons, and streamlines inventory management. This approach is designed to improve customer satisfaction through more accurate searches, real-time suggestions, and a more intuitive shopping experience. Furthermore, Click & Cart presents a scalable solution that can be applied across various platforms, ensuring consistency in both online and mobile shopping environments
Author: Nandini Khandade
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409466160