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This research paper outlines the design and implementation of an innovative AI Fashion Stylist system, integrating cutting-edge technologies to enhance the fashion experience for users. The project encompasses a comprehensive methodology, beginning with data collection and preprocessing, followed by the creation and real-time updating of user profiles. A sophisticated recommendation engine, incorporating collaborative filtering and content-based filtering, is employed for personalized outfit suggestions. The system integrates augmented reality for virtual try-ons, ensuring users can visualize clothing items in real-time. Real-time trend analysis, community engagement features, and seamless shopping assistance further contribute to the platform's depth and relevance. The research emphasizes user feedback mechanisms for continuous improvement, privacy and security considerations, and scalability for optimal performance. This paper offers a concise yet thorough overview of the project's design, demonstrating its commitment to delivering a user-centric, technologically advanced, and engaging AI Fashion Stylist system.
Shete et al. (2024) studied this question.