Abstract

Abstract- Agricultural diseases and insect pests are two of the most significant problems threatening agricultural production. Early detection and identification of pests can significantly reduce pest-related economic losses. In this paper, a convolutional neural network is utilized to identify crop illnesses automatically. The CNN model is utilized for training in this system. The residual network unit to the model has a cross-layer direct edge and multi-layer convolution. The link into the ReLu function activates it when the combined convolution procedure is completed. Calculate the accuracy and create a CNN model. The findings suggest that the system can correctly identify crop plant diseases and Recommended. Keywords: Deep Learning, Image Processing, Classification, Conversational Neural Network etc.