Research Article
Smart Fashion Recommendation System using FashionNet
@ARTICLE{10.4108/eetsis.4278, author={Nagendra Panini Challa and Abbaraju Sao Sathwik and Jinka Chandra Kiran and Kokkula Lokesh and Venkata Sasi Deepthi Ch and Beebi Naseeba}, title={Smart Fashion Recommendation System using FashionNet}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={11}, number={1}, publisher={EAI}, journal_a={SIS}, year={2023}, month={10}, keywords={Deep Learning, ResNet50, KNN, FashionNet}, doi={10.4108/eetsis.4278} }- Nagendra Panini Challa
Abbaraju Sao Sathwik
Jinka Chandra Kiran
Kokkula Lokesh
Venkata Sasi Deepthi Ch
Beebi Naseeba
Year: 2023
Smart Fashion Recommendation System using FashionNet
SIS
EAI
DOI: 10.4108/eetsis.4278
Abstract
An intelligent system known as a fashion suggestion system gives consumers personalised fashion advice based on their tastes, style, body shape, and other variables. The system analyses a user's data and predicts the best fashion products for them using data analytics, machine learning, and artificial intelligence approaches. Intelligent fashion suggestion is currently desperately needed due to the explosive expansion of fashion-focused trends. We create algorithms that automatically recommend users' attire based on their own fashion tastes. We investigate the use of deep networks to this difficult problem. Our technology, called FashionNet, is made up of two parts: a matching network for determining compatibility and a feature network for feature extraction. We create a two-stage training method that transfers a broad compatibility model to a model that embeds personal choice in order to achieve personalised recommendation.
Copyright © 2023 N. P. Challa et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
