Development of an application for the differentiation of the genus of Baird’s sparrow (Centronyx bairdii) based on an artificial neural network

Autor: Francisco García Fernandez, José Hugo Martínez Guerrero, Manuel Armando Salazar Borunda, Daniel Sierra Franco, Martin Emilio Pereda Solis, Luis Antonio Tarango Arámbula
Rok vydání: 2022
Předmět:
Zdroj: Agro Productividad.
ISSN: 2594-0252
2448-7546
DOI: 10.32854/agrop.v14i6.2243
Popis: Objective: To develop a computer application with the possibility of being used in the field with high reliability to differentiate the sex of sparrows of the species Centronyx bairdii. Design/Methodology/Approximation: A previously developed neural network was used to predict the sex of C. bairdii individuals. This algorithm was installed in an application developed using the MATLAB GUIDE environment for using graphic user interfaces. Results: The computer application developed allows the introduction of morphometric data of individuals and predicts their sex with a confidence level of 92.3%. Study Limitations/Implications: To install and run the application it is necessary to have a Windows version 7 operating system or later versions and the Matlab Ver. 7.5.0 software. Findings/Conclusions: Through the computational application generated, it is possible to determine the genus of the species Centronyx bairdii with an accuracy of 92.3%. This is a useful tool for sexing birds of this species in the field.
Databáze: OpenAIRE