Classification System to Detect Diseases in Apples by Using a Convolutional Neural Network

Apples are a great fruit that is well known and is consumed around the world by all people. The importance of having a good quality in these fruits is huge because of to the nutrients for human consumptions and to the versatility that it offers. This work presents a full detection system created by a Convolutional Neural Network (CNN) based on a classifier using Keras that detects the diseases on apples. The CNN presented had an accuracy of the model as 0.7429 after 10 Epochs of training and having the number of data set used for testing of 319 images from 4 different classes. Also, it is described along with a diagram of the architecture where the system is allocated and working in the cloud. Finally, and for the purpose of using the system properly, a mobile app is proposed to be created in order to use the capabilities of the system to detect in a high-speed API by having fast responses when the disease detections are requested through the app.