Style Craft: AI-Driven Fashion Platform
1. ABSTRACT As artificial intelligence continues to reshape industries, personalized and intelligent systems are becoming essential for enriching digital experiences. Style Craft: AI-Driven Fashion Platform introduces a next-generation fashion assistant designed to redefine how users discover, inter...
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| Veröffentlicht in: | INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT Jg. 9; H. 5; S. 1 - 9 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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12.05.2025
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| ISSN: | 2582-3930, 2582-3930 |
| Online-Zugang: | Volltext |
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| Abstract | 1. ABSTRACT As artificial intelligence continues to reshape industries, personalized and intelligent systems are becoming essential for enriching digital experiences. Style Craft: AI-Driven Fashion Platform introduces a next-generation fashion assistant designed to redefine how users discover, interact with, and personalize their style choices. The platform delivers curated fashion recommendations, enables virtual outfit trials, and helps users stay updated with current trends through an intuitive and immersive interface. Built with Python and enhanced by cutting-edge AI methodologies, the system leverages computer vision, natural language understanding, and recommendation engines to offer dynamic suggestions tailored to individual preferences, body profiles, and browsing behavior. Core components include an AI-powered virtual try-on system, style compatibility analysis, and trend forecasting modules, all accessible through a responsive web interface. This paper details the system's architecture and the technologies that power it, emphasizing how AI elevates personalization, visual recognition, and interaction design in the fashion domain. It also addresses implementation challenges, including optimizing garment recognition, adapting to user variability, and maintaining fluid performance. Looking forward, the platform envisions broader capabilities such as conversational AI for voice-guided fashion navigation, AR/VR support for immersive try-ons, and integration with real-time retail inventories for seamless shopping. Style Craft underscores the innovative potential of AI in crafting tailored, engaging, and futuristic fashion experiences for modern users. ACM Reference Format: Mitansh Sehgal, Nikhil Maurya, Abhinav Sinha. 2025. Style Craft: AI-Driven Fashion Platform. Keywords – Artificial Intelligence, Personalized Recommendations, Fashion Technology, , Trend Forecasting, Recommendation Systems, User Personalization, Human-Computer Interaction, Conversational AI, Style Analysis, Intelligent Fashion Assistant, E-commerce Innovation |
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| AbstractList | 1. ABSTRACT As artificial intelligence continues to reshape industries, personalized and intelligent systems are becoming essential for enriching digital experiences. Style Craft: AI-Driven Fashion Platform introduces a next-generation fashion assistant designed to redefine how users discover, interact with, and personalize their style choices. The platform delivers curated fashion recommendations, enables virtual outfit trials, and helps users stay updated with current trends through an intuitive and immersive interface. Built with Python and enhanced by cutting-edge AI methodologies, the system leverages computer vision, natural language understanding, and recommendation engines to offer dynamic suggestions tailored to individual preferences, body profiles, and browsing behavior. Core components include an AI-powered virtual try-on system, style compatibility analysis, and trend forecasting modules, all accessible through a responsive web interface. This paper details the system's architecture and the technologies that power it, emphasizing how AI elevates personalization, visual recognition, and interaction design in the fashion domain. It also addresses implementation challenges, including optimizing garment recognition, adapting to user variability, and maintaining fluid performance. Looking forward, the platform envisions broader capabilities such as conversational AI for voice-guided fashion navigation, AR/VR support for immersive try-ons, and integration with real-time retail inventories for seamless shopping. Style Craft underscores the innovative potential of AI in crafting tailored, engaging, and futuristic fashion experiences for modern users. ACM Reference Format: Mitansh Sehgal, Nikhil Maurya, Abhinav Sinha. 2025. Style Craft: AI-Driven Fashion Platform. Keywords – Artificial Intelligence, Personalized Recommendations, Fashion Technology, , Trend Forecasting, Recommendation Systems, User Personalization, Human-Computer Interaction, Conversational AI, Style Analysis, Intelligent Fashion Assistant, E-commerce Innovation |
| Author | Sinha, Abhinav |
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