Leaf Disease Detection using Machine Learning

Abstract

An essential component of identifying plants for tracking plant growth is plant phenotyping. In this research, an effective method for distinguishing between healthy and sick or infected leaves utilising machine learning algorithms and image processing techniques is presented. Different diseases impact the chlorophyll in leaves, causing brown or black markings on the leaf surface. The productivity of agriculture is largely influenced by the economy. When switching from one disease management strategy to another, farmers experience major difficulties. We are able to recognise or spot tomato leaf diseases, which is the typical method for detection for surveillance and monitoring professionals. Convolutional Neural Networks (CNN) are a type of machine learning technique that are employed in classification.