Detection of citrus leaf diseases using a deep learning technique

The food security major threats are the diseases affected in plants such as citrus so that identification an earlier time is very important. Convenient malady recognition can assist client with responding immediately and sketch for some guarded activities. This be completed without a human by utilizing plant leaf pictures. There many methods employed classification detection machine learning (ML) models, but combination of increasing advances computer vision appears deep (DL) area research to achieve great potential terms accuracy. In this paper, two ways conventional neural networks used named Alex Net Res models data augmentation involves process creating new points manipulating original data. increases number training images DL need add photos, it will appropriate case small datasets. A self-dataset 200 healthy leaves collected. trained give best results 95.83% 97.92% respectively.