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@article{162213,
        author = {Aarya Bhivsanee and Rutuja Vyavhare and Shreya Sonkusare and Sakshi Hadadare},
        title = {Fashion Recommendation System Using Reverse Image Search},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {8},
        pages = {308-313},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=162213},
        abstract = {This paper synthesizes insights from four distinct areas within the realm of fashion recommendation systems. The research encompasses deep learning techniques for style feature decomposition, the utilization of pre-trained convolu- tional neural networks in reverse image searches, categorical image classification employing architectures like ResNet, and the integration of machine learning algorithms in recommendation systems. By amalgamating these diverse approaches, a robust and accurate fashion recommendation system emerges, enhancing user satisfaction and engagement in the digital fashion landscape.},
        keywords = {Neural Networks, Deep Fashion Recommen- dation, Style Features, Convolutional Neural Network Models, Image Classification, ResNet Architecture, Machine Learning Techniques, Fashion Image Retrieval, Image Similarity, Reverse Image Search Analysis, Style Feature Decomposition, Image Recognition, Deep Learning Algorithms, Recommendation Al- gorithms, Pre-processing, Data Mining, Convolutional Layers},
        month = {},
        }