Plant Disease Detection

Abstract

Plant growth is a crucial requirement for farmers since it provides a pathway for their livelihood. Plant damage and growth are correlated with one another. Despite their best efforts, farmers frequently fail to grow healthy crops because of ill plants. Plant disease is currently a dangerous problem for farmers, customers, the environment, and the global economy. Major health problems in plants are caused by excessive pesticide use. Image processing may be the most reliable method of predicting and obtaining precise findings for plant disease diagnosis. Deep convolutional neural networks are used in this research to improve accuracy and training effectiveness. Many uninformed farmers would benefit from our program by receiving accurate disease information that will help them boost their productivity. An online application that can recognize plant illness is something we are fostering. The goal is to identify various plant infections by looking at pictures. We can precisely diagnose plant illness by using the CNN algorithm. The accuracy results demonstrate that this model is superior to any conventional frame.