Shoe Recommendation System Integrating Generative Artificial Intelligence and Convolutional Neural Networks for Image Recognition

We developed a shoe recommendation system that integrates generative artificial intelligence (AI) and convolutional neural networks (CNNs) to enhance image recognition and personalize recommendations. The system utilizes CNNs to accurately identify shoe types from user-uploaded images. Utilizing the...

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Bibliographic Details
Main Authors: Chin-Chih Chang, Chi-Hung Wei, Ray-Nan Liao, Sean Hsiao, Chyuan-Huei Thomas Yang
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Engineering Proceedings
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Online Access:https://www.mdpi.com/2673-4591/92/1/62
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Summary:We developed a shoe recommendation system that integrates generative artificial intelligence (AI) and convolutional neural networks (CNNs) to enhance image recognition and personalize recommendations. The system utilizes CNNs to accurately identify shoe types from user-uploaded images. Utilizing the capabilities of generative AI, the system generates custom shoe suggestions based on weather and location. The proposed system minimizes the need for manual searching but enhances user experience by providing an efficient, automated, and visually driven solution for selecting shoes. The effectiveness of integrating image recognition and generative techniques paves the way for advancements in AI-driven fashion recommendation systems. The developed method offers a powerful tool for increasing customer engagement and satisfaction by delivering personalized and fashion-forward shoe recommendations.
ISSN:2673-4591