Detección de plagas que afectan al tamaño de la musa aab utilizando una aplicación móvil con reconocimiento de imágenes

Early detection of pests in Musa AAB (plantain) is crucial to achieve optimal production. However, farmers' limited experience is a constraint to finding and eliminating these pests. The constant technological advancement and integration of software tools in agriculture allow for solutions for many problems with greater efficiency, as well as minimizing resources. The main goal of this research was to develop a mobile application integrating an image classification model to detect diseases present in banana leaves. To achieve this goal, a literature review was required to identify the most common pests. Subsequently, a set of images of these pests was obtained to train an image classification model. This model was implemented in a native Android mobile application, and a usability test was conducted to evaluate it. The results of the literature review identified 6 pests as the most common. A set of 2856 images was obtained, allowing for the training of the model, which showed a 98% accuracy in pest identification. The mobile application constitutes a positive solution according to the usability test conducted with experts.

• Glavni autor: Mora Vera , Jaime Andres (author)
• Format: bachelorThesis
• Jezik: spa
• Izdano: 2024
• Teme: Plagas; Plátano; Visión por Computadora; CNN; Aplicación móvil
• Online pristup: https://repositorio.uteq.edu.ec/handle/43000/7941