Deep Learning Based Plant Disease Recognition Using Visual Region Approach

Abstract

We identify the plant disease diagnosis using plant disease datasets. In this dataset, plant disease is recognised by means of visual region. Cluster distribution is used to indicate the level of patch with which from each image the weights of divided patches are calculated. Then finally extract the patch features from the trained network and apply the modified deep learning network which is used to bring a panoramic representation.