Plant Disease Detection Using Deep Learning

Abstract

The impact of pests on plants and crops poses significant challenges to agricultural production worldwide. Traditional methods of disease detection, reliant on manual observation by farmers or professionals, are marred by time constraints, high costs, and inaccuracies. In this context, leveraging technological advancements, this study proposes a Disease Recognition Model utilizing leaf image classification to streamline the detection process. Central to our approach is the implementation of Convolutional Neural Networks (CNNs) for image processing, renowned for their effectiveness in pixel input analysis and image recognition tasks. By harnessing CNNs, we aim to develop a robust and efficient system capable of accurately identifying plant diseases from leaf images, thereby offering a promising avenue for optimizing agricultural practices and mitigating crop losses.