Comparison of Classical Computer Vision vs. Convolutional Neural Networks for Weed Mapping in Aerial Images

Authors

  • Paulo César Pereira Júnior Federal University of Santa Catarina
  • Alexandre Monteiro Federal University of Santa Catarina
  • Rafael da Luz Ribeiro Federal University of Santa Catarina
  • Antonio Carlos Sobieranski Federal University of Santa Catarina
  • Aldo von Wangenheim Federal University of Santa Catarina

DOI:

https://doi.org/10.22456/2175-2745.97835

Keywords:

Convolutional Neural Networks, Deep Learning, Digital Image Processing, Precision Agriculture, Semantic Segmentation, Unmanned Aerial Vehicles

Abstract

In this paper, we present a comparison between convolutional neural networks and classical
computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth, for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models

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Author Biographies

Paulo César Pereira Júnior, Federal University of Santa Catarina

Computer Science Post-Graduate Program - PPGCC - Federal University of Santa Catarina

Alexandre Monteiro, Federal University of Santa Catarina

Automation and Systems Engineering Post-Graduate Program

Rafael da Luz Ribeiro, Federal University of Santa Catarina

Brazilian Institute for Digital Convergence

Antonio Carlos Sobieranski, Federal University of Santa Catarina

Department of Computing

Aldo von Wangenheim, Federal University of Santa Catarina

Computer Science Post-Graduate Program - PPGCC - Federal University of Santa Catarina

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Published

2020-12-23

How to Cite

Pereira Júnior, P. C., Monteiro, A., Ribeiro, R. da L., Sobieranski, A. C., & von Wangenheim, A. (2020). Comparison of Classical Computer Vision vs. Convolutional Neural Networks for Weed Mapping in Aerial Images. Revista De Informática Teórica E Aplicada, 27(4), 20–33. https://doi.org/10.22456/2175-2745.97835

Issue

Section

Regular Papers