Plant Disease Detection using Web Application by Neural Network

The fundamental necessity for each country is agricultural products. This affects agricultural productivity in the country and its financial opportunities if plants are afflicted with illnesses. Plant diseases can lead to reduced quality and output of agricultural products. This is highly important for the early detection of plant diseases for global health and well-being. The automatic identification of plant disease becomes an important area of research. It offers benefits in the monitoring of vast fields of crops and helps identify the indications of the illness on the leaves. The leaves contain texture and visual resemblances that are attributable to disease type identification. Therefore, deep learning with computer vision gives way for this problem to be resolved. The article is largely on the determination of plant diseases, reducing crop loss and thus improving the efficiency of production. Our study identifies signs of plant illnesses and diagnoses plant diseases by utilizing the Deep Neural Network (DNN) method based on these symptoms at the very first stage. A hybrid CNN model was utilized to identify plant illness and was demonstrated to outperform it in comparison with standard styles such as AlexNet and LetNet. We have built a web-based AI tool to identify plant disease using this model.