Revolutionizing Agriculture: Detection of Plant Disease using Machine Learning and Deep Learning Algorithms

The threat of plant diseases to global food security highlights the importance of prompt and precise detection. for effective management. Traditional methods are labor-intensive and subjective, prompting the exploration of automated systems. By integrating the advancements in Deep learning and machine learning, this research study investigates the efficacy of algorithms like SVM, Random Forest, CNN, RNN, and ResNet in classifying plant diseases from leaf images. We aim to contribute to enhanced agricultural productivity and food security through automated disease detection.