Detección de severidad de plagas utilizando RNC en cultivo del durazno en Departamento Norte De Santander, Colombia - Andrés Leonardo Castellanos-Corzo; Elizabeth López-Meléndez; Luis David Lara-Rodríguez (Mundo Fesc)
The growing need to increase crop yields in favor of a lower negative burden on the environment has led to the use of crop protection products to prevent the emergence of pests and diseases that generate losses, or quaternary complications that have a greater impact on marketing and production in agriculture. This has led to the generation of technological tools for preventive detection and management of various pests and diseases in agricultural crops. The manuscript presents the use of machine learning techniques such as convolutional neural networks that aid in the detection of Torque and Rust, which are the main impacts on the decline in peach production in the northern region of Santander, Colombia.