STYLESYNC: A FASHION RECOMMENDATION SYSTEM

STYLESYNC: A FASHION RECOMMENDATION SYSTEM

        NehaVarma1,Garima Singh2, Vivek Raj Singh3,

Vineet Swami4,Anushika Tyagi5,Shivam Verma6

 Department of Computer Science And Engineering(Data Science) &

 Department of Computer Science And Engineering(Artificial Intelligence & Machine Learning),

Inderprastha Engineering College, Sahibabad, Ghaziabad, India

Abstract -

Our project focuses on an AI-powered Fashion Recommendation System tailored to assist users in curating outfits for diverse occasions. Users upload clothing images to create individualized wardrobes. Employing machine learning and deep learning, our system accurately classifies clothing types and identifies colors within these images. The core of our innovation lies in a sophisticated recommendation algorithm. By analyzing users' existing wardrobes, including garment types and colors, our algorithm delivers personalized outfit suggestions aligned with users' style preferences and specific event needs. The interface prioritizes user-friendliness, enabling seamless wardrobe management and presenting users with well-matched outfit recommendations. Continuous refinement through user feedback ensures ongoing enhancement of recommendation accuracy, user experience, and machine learning model performance. In summary, our AI-driven Fashion Recommendation

The system aims to streamline the process of dressing for diverse occasions, offering personalized outfit suggestions based on individual wardrobes, thus empowering users with convenient and stylish clothing choices.

Keyword    –         fashion-recommendation, Feature extraction, recommendation system, data analysis, transfer-learning, javascript, python, bootstrap, npm, machine learning, computer vision, deep-learning, reactjs, material-ui, sklearn, Collaborative Filtering, Content-Based Filtering, Deep Learning, Feature Extraction, Natural Language Processing (NLP), Image Recognition.