Co-diseño de una aplicación para el reconocimiento in situ del gorgojo de los andes en cultivos de papa
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Date
2021-12
Journal Title
Journal ISSN
Volume Title
Publisher
LACCEI Inc.
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%.
Description
Keywords
Deep learning, neural network, foliolus, preprocessing, mobile application