Sugarcane diseases in Peru occur due to the agricultural community's lack of understanding of these, which means a slow response to the application of methods of control and eradication of these diseases; thus, causing economic losses and underproduction. Due to the aforementioned, a web application for sugarcane diseases recognition is proposed. The five types of sugarcane diseases that will be recognized using this system are: Pineapple Sett Rot, Ring Spot, Mosaic, Brown Rust and Leaf Scorch. This system was developed using GoogLeNet, which is a 22 layers convolutional neural network (CNN), and also the Matlab software and its App Designer extensions (for the web application creation); additionally, Matlab Web App Server was used to host the application on the web. The pre-trained neural network developed in Matlab based on the GoogLeNet architecture allowed the creation and configurat...