An Investigation of Parameter Optimization in Fingerling Counting Problems - Oliveira Junior, Adair da Silva; Pache, Marcio Carneiro Brito; Rezende, Fábio Prestes Cesar; Sant’Ana, Diego André; Weber, Vanessa Aparecida de Moraes; Astolfi, Gilberto; Weber, Fabricio de Lima; Menezes, Geazy Vilharva; Menezes, Gabriel Kirsten; Albuquerque, Pedro Lucas França; Costa, Celso Soares; Garcia, Vanir; et al. (Anais do Workshop de Visão Computacional (WVC), 2021)
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.