Plant leaf diseases classification using Deep Learning

As the world’s population expands, securing global food security has taken on greater importance. The early detection and prevention of plant diseases, which can have catastrophic impacts on agricultural yields and food supplies, is one of the biggest challenges facing farmers. The ability to automatically identify and categorize plant diseases based on visual signs has been made possible in recent years thanks to advancements in computer vision and deep learning.This article examines the most recent deep learning models and image processing techniques for computer vision-based plant disease classification.The Xception and GoogleNet networks are linked to Global Average Pooling, and then the outputs are combined and passed to the classification phase to give a single neural network. The suggested network’s total average accuracy across all classes is 98.76%.