Year: 2025
Type: article
Abstract: ABSTRACT - Plant diseases pose a critical challenge to agricultural productivity worldwide. Early and accurate diagnosis of plant diseases is essential for ensuring food security and minimizing economic losses. This project presents a deep learning-based solution to detect plant diseases using Convolutional Neural Networks (CNNs). The model is trained on a dataset of plant leaf images, including various healthy and tdiseased conditions. The proposed system preprocesses input images, extracts features using CNN layers, and classifies them into predefined disease categories. Experimental results demonstrate that the model achieves high accuracy and outperforms traditional manual methods. The final system is deployed as a standalone application, providing an efficient and user-friendly platform for disease diagnosis.
DOI: 10.55041/ijsrem45994
Author: Mrs. SAHANA R S
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: bronze
OpenAlex ID: W4409811666