Plant/Crop Disease Detection using Artificial Neural Networking

Abstract

This new approach would come in handy to enhance the quality and also to protect the crops in the agricultural sector. The most fundamental step for the detection of plant diseases by using a recognition model powered by deep convolutional network training was to search and gather correct information about the various plant and crop diseases from several reliable sources, most notably digital libraries and government sources. The results obtained are highly accurate as the model using CNN distinguishes the diseased leaves clearly from the healthy leaves. The information gathered from various libraries and databases in addition to agricultural experts provided a diverse and powerful database which in conjunction with the deep convolutional training model would be a major advancement in this field. Keras will be used for implementing the neural networks in order to attain the highest possible accuracy.