Desarrollo de una herramienta computacional basada en redes neuronales para el diagnóstico del tizón tardío en cultivos de papa
Loading...
Share
Date
2021-06-10
Authors
Director(s)
Publisher
Universidad Antonio Nariño
Campus
Degree obtained
Document type
COAR type
http://purl.org/coar/resource_type/c_bdcc
Citation
Bibliographic Managers
Document Viewer
Select a file to preview:
item.page.resume
Abstract
Late blight (Phythottora Infestas) is a disease that seriously affects potato crops, causing
a negative impact on the farmer's economy. This project will generate a computational tool called NeuroPI - 2105 based on a convolutional neural network created by the author, which classifies two types of leafs that are; healthy and sick. The network has been trained
with 1304 images from the PlantVillage database, 304 of them correspond to healthy
leaves, the remainder being attributed to late blight. The training algorithm has used the
Adam gradient descent, the cross-entropy error function, and backpropagation, in order to adjust the synaptic weights and threshold levels in the network.