Explorando bases de dados para treinamento de modelos em aprendizagem de máquina na indústria da moda
DOI:
https://doi.org/10.29147/datjournal.v9i2.877Palavras-chave:
Aprendizagem de Máquina na Moda, Inteligência Artificial, Inovação tecnológica, Base de dados, Aprendizagem supervisionadaResumo
O interesse crescente na aplicação da aprendizagem de máquina (AM) na moda destaca a importância do uso de dados rotulados para desenvolver modelos, facilitando a replicação de pesquisas e automatizando a análise de novos dados, como imagens de desfiles de moda disponíveis online. Apesar dessa necessidade, poucos estudos, especialmente no Brasil, exploram metodologicamente a interseção entre moda e AM. Esta pesquisa visa oferecer uma visão geral das bases de dados online para treinamento de modelos de AM. Uma revisão sistemática identificou 26 artigos que utilizam essas bases de dados, como Fashion-MNIST e DeepFashion2. A análise de conteúdo revelou que essas bases, incluindo Polyvore e Fashion Image Dataset, têm aplicações diversas, destacando o potencial transformador da AM na moda e incentivando inovações em design, produção e marketing na indústria da moda.
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