Artificial Intelligence in Automated Sorting in Trash Recycling

  • Bernardo S. Costa IFSuldeMinas
  • Aiko C. S. Bernardes IFSuldeMinas
  • Julia V. A. Pereira IFSuldeMinas
  • Vitoria H. Zampa IFSuldeMinas
  • Vitoria A. Pereira IFSuldeMinas
  • Guilherme F. Matos IFTM
  • Eduardo A. Soares UFSCAR
  • Claiton L. Soares IFTM
  • Alexandre F. Silva IFSuldeMinas
DOI: https://doi.org/10.5753/eniac.2018.4416

Resumo


A computer vision approach to classify garbage into recycling categories could be an efficient way to process waste. This project aims to take garbage waste images and classify them into four classes: glass, paper, metal and, plastic. We use a garbage image database that contains around 400 images for each class. The models used in the experiments are Pre-trained VGG-16 (VGG16), AlexNet, Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and, Random Forest (RF). Experiments showed that our models reached accuracy around 93%.

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Publicado
22/10/2018
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COSTA, Bernardo S. et al. Artificial Intelligence in Automated Sorting in Trash Recycling. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 15. , 2018, São Paulo. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2018 . p. 198-205. ISSN 2763-9061. DOI: https://doi.org/10.5753/eniac.2018.4416.