FashionDesignAI: AI-Based Fashion Recommendation and Styling Platform
Akshatha Prashanth
Dept. of MCA
RV College of Engineering Bengaluru, India akshathap.mca24@rvce.edu.in
Pragathi H R
Dept. of MCA
RV College of Engineering Bengaluru, India pragathihr.mca24@rvce.edu.in
Dr. Savitha R
Assistant Professor, Dept. of MCA
RV College of Engineering
Bengaluru, India savithar@rvce.edu.in
Abstract— Artificial intelligence technology is being used by digital platforms to track market trends, create personalized experiences, and improve user engagement, which causes the fashion industry to change quickly. Because their design relies on users choosing fashion items through manual tagging, static filters, and past purchase patterns, fashion recommendation systems encounter difficulties. Because users require specific outfit advice that takes into account their upcoming events, physical characteristics, and style preferences, the systems are unable to offer useful styling recommendations.
In order to handle situations that arise during their current established boundaries, users of current fashion platforms must perform extensive manual product comparisons, which causes cognitive overload. Users must visualize appropriate outfit combinations and comprehend how their clothing items fit their personal style, seasonal context, and color compatibility. Because consumers must make decisions without intelligent styling assistance, online fashion experiences have three detrimental effects.
The researchers developed a FashionDesignAI Recommendation and Styling Platform which uses machine learning and modern web technologies to deliver customized outfit recommendations for FashionDesignAI Recommendation and Styling Platform. The system generates fashion recommendations by assessing multiple user factors which include their gender and body shape and the specific event and their selected colors and current fashion trends. The platform operates as a virtual styling assistant which uses user preferences and interactive browsing and outfit visualization to guide users in making informed fashion choices.
The proposed solution enhances online fashion platforms through its dual implementation of data-driven intelligence and user-focused design elements. The system serves e-commerce fashion websites and virtual styling applications and academic research into AI recommendation systems because it provides personalized user experiences with minimal decision-making requirements. The platform demonstrates artificial intelligence applications which improve digital fashion experiences through better quality and accessibility and wider application range.
Index Terms—Artificial Intelligence, Fashion Recommendation, Machine Learning, Personalization, Web Application, Styling System
