Bell Pepper Leaf Disease Classification Using CNN

Abstract

In classifying various plant diseases, Great success has been achieved through deep learning with convolutional neural networks (CNNs). This paper offers an overview analysis of current plant-based disease detection systems. In this analysis, using a CNN, equipped with a bell pepper plant image dataset, a variety of simulation approaches for neurons and layers were used. Plant diseases cause significant growth and economic losses, as well as a reduction in the quality and quantity of agricultural products. In monitoring large crop fields, the detection of plant diseases in a day has received increasing attention. Good plant health and disease identification data through effective management strategies may promote disease control. This approach would increase the production of crops. Bugs known as aphids spread viruses. That's why control of insects is so important to control pepper plant problems. Pepper-related diseases will devastate your entire garden like a virus or wilt. When you find issues with the pepper crop, the best thing to do is destroy the infected plant before it infects the entire garden. As it is understood Once trained on larger datasets, convolutional networks may learn features, there is no need to worry about image quality.