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Co-diseño de una aplicación para el reconocimiento in situ del gorgojo de los andes en cultivos de papa

Published in: Ideas to Overcome and Emerge from the Pandemic Crisis: Proceedings of the 1st LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development
Date of Conference: December 9-10, 2021
Location of Conference: Virtual
Authors: Liliana Fernández Samacá (Universidad Pedagógica y Tecnológica de Colombia, CO)
Oscar Iván Higuera Martínez (Universidad Pedagógica y Tecnológica de Colombia, CO)
Lorena María Alarcón Aranguren (Universidad Pedagógica y Tecnológica de Colombia, CO)
Andrés Felipe Merchán Dehaquiz (Universidad Pedagógica y Tecnológica de Colombia, CO)
Félix Daniel Valderrama Pineda (Universidad Pedagógica y Tecnológica de Colombia, CO)
Full Paper: #42

Abstract:

Various methods are employed to prevent potato crops from being affected by diseases and pests, one of which is monitoring, which consists of people walking through the crops and using their cognitive abilities to recognize the presence of pests. However, limitations in human capacity such as inaccuracy due to the subjectivity introduced by the farmer can cause failures in the diagnosis. For this reason, a system capable of detecting the presence of the Andean weevil was implemented. For this purpose, artificial vision is used to perform the preprocessing of images extracted from photographs provided by farmers. In addition, a deep learning model based on the VGGNet architecture was developed. The architecture was taken to a mobile application using the model called MobileNet. The results showed an adequate recognition rate, obtaining a prediction accuracy of up to 84%.