Year: 2025
Type: article
Abstract: Plant diseases pose a significant threat to global agricultural production, leading to substantial economic losses and food shortages.Traditional disease identification methods require expert knowledge and are often time-consuming.With advancements in artificial intelligence, deep learning-based automated plant disease classification has become a promising solution.This study presents a convolutional neural network (CNN) model trained on the PlantVillage dataset using Python, TensorFlow, and Kera's to classify plant diseases based on leaf images.The model achieves an accuracy of over 95%, demonstrating its effectiveness.The paper discusses data preprocessing, model architecture, training strategies, and performance evaluation.Future improvements and deployment strategies are also addressed.
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: hybrid
OpenAlex ID: W4411310375