Published Paper Details:

Nowadays plant disease is becoming more and more serious in the agriculture, farmers suffer a lot due to the infection, drastic climate changes and lack of immunity in crops and their yield is also affected due to the lack of detection. This causes large scale demolition of crops, decreases cultivation and eventually leads to financial loss of farmers. Due to rapid growth in variety of diseases and adequate knowledge of farmer, identification and treatment of the disease has become a major challenge. The leaves have texture and visual similarities which attributes for identification of disease type. Hence, computer vision employed with deep learning which provides the way to solve this problem. This paper proposes a deep learning-based CNN model which is trained using plant village dataset containing various images of healthy and diseased leaves. The performance of the proposed model is compared with the existing model and result is presented in the section