Hybrid Model to Predict Leaf Disease Prediction Using Ensembling Machine Learning Approach

Abstract

In this work, the use of machine learning to forecast instances of leaf disease is advocated. The automated leaf disease detection system used in precision agriculture makes use of camera input, computer vision processing, picture segmentation, feature extraction, and machine learning. A rapid and precise diagnosis of plant disease is made possible by an automated disease detection system for the benefit of the farmer. In order to speed up crop diagnosis, it is crucial to use an automated method for detecting plant leaf diseases.

Topics & Concepts