An Investigation of Parameter Optimization in Fingerling Counting Problems

  • Adair da Silva Oliveira Junior UFMS
  • Marcio Carneiro Brito Pache UCDB / IFMS
  • Fábio Prestes Cesar Rezende UCDB
  • Diego André Sant’Ana UCDB / IFMS
  • Vanessa Aparecida de Moraes Weber UCDB / UEMS
  • Gilberto Astolfi UFMS / IFMS
  • Fabricio de Lima Weber UEMS
  • Geazy Vilharva Menezes UFMS
  • Gabriel Kirsten Menezes UFMS
  • Pedro Lucas França Albuquerque University of Nebraska
  • Celso Soares Costa UCDB / IFMS
  • Vanir Garcia UCDB / IFMS
  • Eduardo Quirino Arguelho de Queiroz UCDB
  • João Victor Araújo Rozales UCDB
  • Milena Wolff Ferreira UCDB
  • Marco Hiroshi Naka UCDB / IFMS
  • Hemerson Pistori UCDB

Resumo


The objective of this paper is to investigate which combination of parameters for the fingerling counting software results in the smallest Mean Absolute Error (MAE) and smallest Root Mean Squared Error (RMSE). For this, an image dataset called FISHCV155V was created and separated into training and test sets, where different combinations of parameters for the software were tested. From the obtained results were extracted individual performance metrics for each combination of parameters, such as MAE, Mean Square Error (MSE) and RMSE. Video frames were analysed comparing the parameter combination that obtained the best and worst results, in order to investigate the influence of such parameters in the performance of the software. From such results, it was concluded that the best combination reached 5.99 MAE and 9.96 RMSE.

Palavras-chave: image/video analysis, automated counting, parameterization, computer vision

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Publicado
22/11/2021
OLIVEIRA JUNIOR, Adair da Silva et al. An Investigation of Parameter Optimization in Fingerling Counting Problems. In: WORKSHOP DE VISÃO COMPUTACIONAL (WVC), 17. , 2021, Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 7-12. DOI: https://doi.org/10.5753/wvc.2021.18881.

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