One of the many strands of AI includes "deep learning". According to this research, Autonomous learning and feature extraction have made it a hot topic in academia and industry in recent years. Images, videos, and speech and natural language processing have all benefited from it. Agriculture plant disease and pest range assessment research is also being conducted locally. Artificially selected disease spot features may have limitations, but deep learning can help overcome these problems by enhancing both the adequacy of plant disease recognition models that use deep learning as well as the objectivity of feature extraction. Agricultural leaf disease identification using deep learning technologies is summarized in this paper. In order to detect plant leaf illness, we used deep learning and high-resolution imaging techniques within the scope of this study. A Convolutional Neural Network (CNN) algorithm was employed here (CNN). The level of accuracy can be reached can be increased to 95% by repetitive iterations.

Convolutional Neural Network, Machine Learning Techniques, Deep Learning Technology.