TY - GEN
T1 - Towards automatic classification of mosquito species based on wing geometrical features
AU - Carrillo, Dennis
AU - Benitez, Diego S.
AU - Ramon, Giovanni
AU - Perez, Noel
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/13
Y1 - 2020/10/13
N2 - 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.
AB - 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.
KW - Automated classification
KW - Geometrical features
KW - Mosquito species
KW - Supervised learning
UR - http://www.scopus.com/inward/record.url?scp=85098589815&partnerID=8YFLogxK
U2 - 10.1109/ANDESCON50619.2020.9271981
DO - 10.1109/ANDESCON50619.2020.9271981
M3 - Contribución a la conferencia
AN - SCOPUS:85098589815
T3 - 2020 IEEE ANDESCON, ANDESCON 2020
BT - 2020 IEEE ANDESCON, ANDESCON 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE ANDESCON, ANDESCON 2020
Y2 - 13 October 2020 through 16 October 2020
ER -