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.
Article Details
Unique Paper ID: 162213
Publication Volume & Issue: Volume 10, Issue 8
Page(s): 308 - 313
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