Comparative Analysis of Plant Disease Detection System

Author(s)	Mr. Akshint Varma, Mr. Dhruv Kumar, Mr. Prathamesh Sanjay Date, Mr. Pranav Dipke, Prof. Sweta Wankhade
Country	India
Abstract	Plant diseases pose a critical threat to global agriculture, necessitating rapid and precise detection methods. In this study, we present an enhanced deep learning framework for plant disease detection that outperforms existing benchmarks by integrating refined preprocessing, advanced feature extraction, and optimized classification techniques. Our model achieves superior accuracy and generalization across diverse disease categories, as confirmed by standard evaluation metrics, while addressing limitations of previous approaches such as sensitivity to low-quality images and class imbalance. These improvements offer a robust tool for real-world agricultural monitoring with potential applications in precision farming and scalable crop health management.
Keywords	Plant disease detection, deep learning, classification techniques, model building, image processing, comparative analysis
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-05-20
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.45313
Short DOI	https://doi.org/g9kvdw

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International Journal For Multidisciplinary Research