Towards automatic classification of mosquito species based on wing geometrical features

Dennis Carrillo, Diego S. Benitez, Giovanni Ramon, Noel Perez

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

This paper presents an initial version of a system for the automated classification of mosquitoes species, based on relevant features extracted from their wing's morphology. The algorithm developed allows identifying the mosquito's species by using key reference points of the wing, such as the radio of the circular geometries of spots presents within the wing. The aim was to develop an initial version of a system for improving the standard manual method in which mosquitoes are classified, as a proof of concept. For testing the system, two particular species: Limatus durhamii and Wyeomyia sp. were used for classification using a simple perceptron. The model reached an accuracy value of 95.46% in predicting new wing samples. Initial results indicate that with future refinements, an automated classification system is feasible.

Idioma originalInglés
Título de la publicación alojada2020 IEEE ANDESCON, ANDESCON 2020
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728193656
DOI
EstadoPublicada - 13 oct. 2020
Evento2020 IEEE ANDESCON, ANDESCON 2020 - Quito, Ecuador
Duración: 13 oct. 202016 oct. 2020

Serie de la publicación

Nombre2020 IEEE ANDESCON, ANDESCON 2020

Conferencia

Conferencia2020 IEEE ANDESCON, ANDESCON 2020
País/TerritorioEcuador
CiudadQuito
Período13/10/2016/10/20

Huella

Profundice en los temas de investigación de 'Towards automatic classification of mosquito species based on wing geometrical features'. En conjunto forman una huella única.

Citar esto