• Geetanshu Patil
• Aastha Patil
• Shital Kanojiya
• Aditya Hirekhan
• Aditya Ramteke

The rapidly growing sectors of Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing various industries, particularly fashion. A primary hurdle in online apparel retail is consumer uncertainty regarding size, fit, and style. This often results in dissatisfaction, diminished conversion rates, and high return rates. To mitigate this, we present an ML-driven Outfit Suggestion System. This system utilizes deep learning and computer vision to deliver personalized clothing recommendations, tailored to individual body proportions and style preferences. The system comprises two key modules: a computer vision-based body shape analysis module and a deep learning-powered clothing feature extraction model. The body shape analysis module processes user-submitted images, extracting attributes like shoulder width, waist-to-hip ratio, and overall proportions. Deep learning categorizes users into predefined body types (pear, hourglass, rectangle, etc.), ensuring personalized recommendations. The clothing feature extraction model, using a pretrained CNN (e.g., ResNet50), analyzes a vast apparel database, identifying attributes such as fabric, pattern, and fit. This allows the system to determine flattering styles for various body types. Furthermore, k-Nearest Neighbors (k-NN) clustering and collaborative filtering are employed to recommend clothing based on similarity metrics, incorporating both body proportions and user preferences. This hybrid approach ensures relevant suggestions. Integrating AI-driven body shape analysis with deep learning-based recommendations enhances the online shopping experience by providing personalized, accurate, and visually appealing outfit suggestions, thereby reducing uncertainty, boosting consumer confidence, minimizing returns, and improving e-commerce efficiency. As intelligent fashion recommendation systems gain prominence, our approach offers a scalable solution for retailers seeking to enhance user satisfaction and streamline their platforms

Machine Learning ML, AI Fashion Recommendation, Computer Vision Body Shape Analysis, Deep Learning Clothing Feature Extraction, Personalized Outfit Suggestion.

"A Personalized Style Guide", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.b285-b288, May-2025, Available :http://www.jetir.org/papers/JETIR2505134.pdf

"A Personalized Style Guide", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppb285-b288, May-2025, Available at : http://www.jetir.org/papers/JETIR2505134.pdf