Open AccessAn Investigation of Parameter Optimization in Fingerling Counting Problems
Author(s) -
Adair da Silva Oliveira,
Marcio Carneiro Brito Pache,
Fábio Prestes Cesar Rezende,
Diego André Sant’Ana,
Vanessa Weber,
Gilberto Astolfi,
Fabricio de Lima Weber,
Geazy Vilharva Menezes,
Gabriel Kirsten Menezes,
Pedro Lucas França Albuquerque,
Celso Soares Costa,
Vanir Garcia,
Eduardo Quirino Arguelho de Queiroz,
João Victor Araújo Rozales,
Milena Wolff Ferreira,
Marco Hiroshi Naka,
Hemerson Pistori
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/wvc.2021.18881
Subject(s) - mean squared error , mean absolute error , mathematics , software , statistics , root mean square , mean squared prediction error , algorithm , computer science , engineering , electrical engineering , programming language
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.