App2: software solution for apple leaf disease detection based on deep learning (CNN+SVM).

ABSTRACT: Early detection of crop diseases is essential to reduce yield losses and improve management efficiency in agricultural production. This work presents the development of a mobile application, called App2, designed to detect diseases in apple tree leaves from images taken or uploaded by the user. The solution integrates a hybrid model based on a Convolutional Neural Network (CNN) and a Support Vector Machine (SVM), developed for computer vision tasks focused on recognizing diseases in apple leaves. The system architecture includes a user interface built with React Native, an API developed using FastAPI and deployed on Azure, and a pre-filter implemented through the OpenAI API to validate that the uploaded images correspond to crop leaves. The model was trained to classify images into six cat

SUBMITTER: Arones E 

PROVIDER: S-EPMC12568702 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature