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An Evaluation of Image Preprocessing in Skin Lesions Detection

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Detalhes bibliográficos
Resumo:This study aims to evaluate the impact of image preprocessing techniques on the performance of Convolutional Neural Networks (CNNs) in the task of skin lesion classification. The study is made on the ISIC 2017 dataset, a widely used resource in skin cancer diagnosis research. Thirteen popular CNN models were trained using transfer learning. An ensemble strategy was also employed to generate a final diagnosis based on the classifications of different models. The results indicate that image preprocessing can significantly enhance the performance of CNN models in skin lesion classification tasks. Our best model obtained a balanced accuracy of 0.7879.
Autores principais:Silva, Giuliana Martins
Outros Autores:Lazzaretti, André E.; Monteiro, Fernando C.
Assunto:Skin Lesion Classification Convolutional Neural Networks Deep Learning Image Preprocessing
Ano:2024
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso restrito
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB

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