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AI-powered Body Type Analysis for Fashion Recommendation System

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  • Sallar Sami, Bushra Khan, Safiullah, Zafar Ali, Atta ur Rehman, Naseeb Ullah, Shahzaib Ali

    (Department of Computer Science Quaid-e-Awam University of Engineering Science and Technology, Nawabshah)

Abstract

This paper presents an AI-powered fashion recommendation system that analyzes body types to offer personalized clothing suggestions. The system uses Convolutional Neural Networks (CNN) to classify male body shapes into three categories (ectomorph, mesomorph, endomorph) and matches them with suitable fashion items. We developed a web-based platform using the React-Django framework, allowing users to upload photos, receive a body type analysis, and get customized fashion advice. Testing shows our approach achieves a 94% success rate in body type classification, significantly outperforming existing methods. This study addresses a key gap in current fashion recommendation systems, which often overlook body type considerations for men. Our solution provides an effective and user-friendly way to enhance online shopping and build greater trust in fashion choices

Suggested Citation

  • Sallar Sami, Bushra Khan, Safiullah, Zafar Ali, Atta ur Rehman, Naseeb Ullah, Shahzaib Ali, 2025. "AI-powered Body Type Analysis for Fashion Recommendation System," International Journal of Innovations in Science & Technology, 50sea, vol. 7(6), pages 196-200, May.
    • Handle: RePEc:abq:ijist1:v:7:y:2025:i:6:p:196-200
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