International Journal Of Imaging

Abstract

Enhancing crop health monitoring for e-Agricultureprediction of Apple leaf diseases using deep learning

Author: Chowdavarapu Sai Vennela, Bonagiri Sakyath , Jatavath Mahesh Babu , Mr. K. Hari Krishna

Abstract:

Agriculture is a crucial sector for global food security, and plant health plays a vital role in ensuring high-quality crop yields. The early detection of plant diseases can help in reducing losses and improving productivity. Traditional disease identification methods rely on manual inspection, which is time-consuming and prone to errors. In recent years, deep learning techniques have emerged as powerful tools in image classification and pattern recognition. This project focuses on leveraging deep learning for the detection and classification of apple leaf diseases. The proposed model utilizes Convolutional Neural Networks (CNNs) trained on a dataset of diseased and healthy apple leaves to classify infections with high accuracy. By integrating AI into e-agriculture, this project aims to enhance real-time crop health monitoring, enabling farmers to take preventive measures and optimize yield quality.