Aplicação de Redes de Inteligência Artificial e Técnicas de Aprendizado de Máquina no Combate de Inseto-Pragas nas Folhagens de Soja: O Caso das Lagartas Caterpillar e Diabrotica Speciosa

Abstract

This study analyzes the application of artificial intelligence networks and machine learning techniques to combat pests in soybean foliage, focusing on Caterpillar and Diabrotica speciosa larvae. The study uses TensorFlow, an open-source library developed by Google Brain, to comparatively evaluate the effectiveness of artificial intelligence and machine learning-based solutions in pest classification. The goal is to contribute to the development of more effective methods for monitoring and managing diseases in soybean crops, aiming to reduce agricultural losses. Challenges include the accuracy in identifying pests in images collected by drones and smartphones, as well as the efficient implementation of machine learning algorithms. This study aims to provide valuable insights to enhance agricultural practices.