Plant Disease Detection System : Based on Machine Learning (CNN)

Plant Disease Detection System : Based on Machine Learning (CNN)

Shubham Singh

CSE Department SRMCEM LUCKNOW,INDIA shubham11.07.02@gmail.com

Siddharth Singh

CSE Department SRMCEM LUCKNOW,INDIA be20cs107siddharthsingh@ gmail.com

Er. Aayush Pratap Singh (Assistant Professor)

CSE Department SRMCEM LUCKNOW,INDIA

Abstract— One of the important and tedious task in agricultural practices is detection of disease on crops. It requires huge time as well as skilled labor. To mitigate this issue, computer aided disease recognition model is proposed. It uses leaf image classification with the help of deep convolutional networks. In this paper, VGG16 and Resnet34 CNN was proposed to detect the plant disease. It has three processing steps namely feature extraction, downsizing image and classification. In CNN, the convolutional layer extracts the feature from plant image. The pooling layer downsizing the image. The disease classification was done in dense layer. The proposed model can recognize 38 differing types of plant diseases out of 14 different plants with the power to differentiate plant leaves from their surroundings. The performance of VGG16 and Resnet34 was compared. The accuracy, sensitivity and specificity was taken as performance Metrix. It helps to give personalized recommendations to the farmers based on soil features, temperature and humidity.

Keywords—Plant disease, Convolutional neural network, VGG16, Resnet34, leaf image , Image Processing.