Plant Detection and Give its Detail Using AI

The field of artificial intelligence includes deep learning. The benefits of AI and feature extraction have made it a hot topic in both academia and business in recent years. Many applications in the fields of speech recognition, image processing, and natural language processing have made extensive use of it. Additionally, it has emerged as a center of excellence for research on agricultural plant protection, including pest range assessment, plant disease recognition, and more. Deep learning’s usage in plant disease recognition has the potential to increase research efficiency, speed up technological transition, make plant disease feature extraction more objective, and prevent the drawbacks of artificially selecting disease spot features. This article summarizes the latest developments in the use of deep learning for the purpose of identifying diseases in crop leaves. Using the deep learning and advanced imaging techniques of CenterNEt ResNET, we highlight the current trends and problems in plant leaf disease identification in this research. We anticipate that this work will serve as an invaluable tool for scientists whose focus is on finding pest insects and illnesses in plants. At the same time, we also discussed some of the current challenges and problems that need to be resolved.