Plant Leaf Disease Detection Through CNN

Computer Engineering

The goal of this research is to explore the application of Convolutional Neural Networks (CNNs) in the detection of plant leaf diseases. Plant diseases significantly impact agricultural productivity, leading to economic losses and food insecurity. Early detection and accurate diagnosis of these diseases are crucial for timely intervention and effective management. Traditional methods of disease detection are often labor-intensive and time-consuming. In recent years, deep learning techniques, particularly CNNs, have shown promising results in automating disease detection processes. This study provides a comprehensive overview of plant leaf diseases, discusses the fundamentals of CNNs, reviews relevant literature on the application of CNNs in plant disease detection, presents a methodology for implementing CNN-based disease detection models, analyzes the results obtained, and concludes with insights into the efficacy and potential challenges of CNN-based approaches in plant disease diagnosis.

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