Adair da Silva Oliveira Junior, M. Pache, Fábio Prestes Cesar Rezende, D. Sant’Ana, V. Weber, Gilberto Astolfi, F. Weber, G. Menezes, Gabriel Kirsten Menezes, Pedro Lucas França Albuquerque, Celso Soares Costa, Vanir Garcia, Eduardo Quirino Arguelho de Queiroz, João Victor Araújo Rozales, M. Ferreira, M. Naka, H. Pistori
{"title":"鱼种计数问题中参数优化的研究","authors":"Adair da Silva Oliveira Junior, M. Pache, Fábio Prestes Cesar Rezende, D. Sant’Ana, V. Weber, Gilberto Astolfi, F. Weber, G. Menezes, Gabriel Kirsten Menezes, Pedro Lucas França Albuquerque, Celso Soares Costa, Vanir Garcia, Eduardo Quirino Arguelho de Queiroz, João Victor Araújo Rozales, M. Ferreira, M. Naka, H. Pistori","doi":"10.5753/wvc.2021.18881","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":311431,"journal":{"name":"Anais do XVII Workshop de Visão Computacional (WVC 2021)","volume":"343 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Investigation of Parameter Optimization in Fingerling Counting Problems\",\"authors\":\"Adair da Silva Oliveira Junior, M. Pache, Fábio Prestes Cesar Rezende, D. Sant’Ana, V. Weber, Gilberto Astolfi, F. Weber, G. Menezes, Gabriel Kirsten Menezes, Pedro Lucas França Albuquerque, Celso Soares Costa, Vanir Garcia, Eduardo Quirino Arguelho de Queiroz, João Victor Araújo Rozales, M. Ferreira, M. Naka, H. Pistori\",\"doi\":\"10.5753/wvc.2021.18881\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":311431,\"journal\":{\"name\":\"Anais do XVII Workshop de Visão Computacional (WVC 2021)\",\"volume\":\"343 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Anais do XVII Workshop de Visão Computacional (WVC 2021)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5753/wvc.2021.18881\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anais do XVII Workshop de Visão Computacional (WVC 2021)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5753/wvc.2021.18881","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Investigation of Parameter Optimization in Fingerling Counting Problems
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.
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