Análise Comparativa de Versões YOLO na Detecção e Identificação de Parasitas da Malária

  • Maura G. R. Rocha UFPI
  • Rodrigo M. S. Veras UFPI
  • Maíla L. Claro UFPI
  • Laurindo S. Britto Neto UFPI
  • Kelson R. T. Aires UFPI

Resumo


A malária é uma doença endêmica causada pelo parasita Plasmodium que pode ser fatal em muitas regiões do mundo. Alguns pesquisadores estão utilizando conceitos de aprendizagem de máquina para detectar e classificar células infectadas pelo parasita Plasmodium. Este trabalho apresenta um estudo comparativo de três versões recentes da rede neural convolucional You Only Look Once (YOLO), são elas a: YOLOv4, Scaled-YOLOv4 e YOLOv5. Foi utilizado a base de dados MP-IDB que possui 210 imagens com o parasita Plasmodium. Os modelos alcançaram excelentes resultados, tendo o melhor resultado com mAP e precisão de 94,8% e 93,3%, respectivamente, para a classificação em dois tipos de espécies do Plasmodium falciparum e vivax.

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Publicado
15/06/2021
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ROCHA, Maura G. R.; VERAS, Rodrigo M. S.; CLARO, Maíla L.; BRITTO NETO, Laurindo S.; AIRES, Kelson R. T.. Análise Comparativa de Versões YOLO na Detecção e Identificação de Parasitas da Malária. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 21. , 2021, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 212-223. ISSN 2763-8952. DOI: https://doi.org/10.5753/sbcas.2021.16066.

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