MosCla app: An android app to classify Culicoides species

Sebastian Gutierrez, Noel Perez, Diego S. Benitez, Sonia Zapata, Denis Augot

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

Resumen

Culicoides biting midges are transmission vectors of various diseases affecting humans and animals around the world. An optimal and fast classification method for these and other species have been a challenge and a necessity, especially in areas with limited resources and public health problems. In this work, we developed a mobile application to classify two Culicoides species using the morphological pattern analysis of their wings. The app implemented an automatic classification method based on the calculation of seven morphological features extracted from the wing images and a support vector machine classifier to produce the final classification of Pusillus or Obsoletus class. The proposed app was validated on an experimental dataset with 87 samples, reaching an outstanding mean of AUC score of 0.98 in the classification stage. Besides, we assessed the app feasibility using the mean of time and battery consumption metrics on two different emulators. The obtained scores of 12 and 7 s and 0.11 and 0.03 mAh for the phone and tablet emulators are satisfactory when developing mobile applications. Finally, reducing the feature space using an external wrapper method provided us a considerable improvement in the classification performance, AUC scores from 0.95 to 0.98, and decreasing the volume of information in training stages. Thus, these results enable the proposed app as an excellent approximation to those specialists that need a practical tool to classify Pussillus or Obsoletus species in wildlife environments.

Idioma originalInglés
Título de la publicación alojada2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings
EditoresAlvaro David Orjuela-Canon
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728194066
DOI
EstadoPublicada - 7 ago. 2020
Evento2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Virtual, Cali, Colombia
Duración: 7 ago. 20209 ago. 2020

Serie de la publicación

Nombre2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings

Conferencia

Conferencia2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020
País/TerritorioColombia
CiudadVirtual, Cali
Período7/08/209/08/20

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