Convolutional Neural Networks in Detection of Plant Leaf Diseases: A Review

Rapid improvements in deep learning (DL) techniques have made it possible to detect and recognize objects from images. DL approaches recently entered various agricultural farming applications after being successfully employed fields. Automatic identification of plant diseases can help farmers manage their crops more effectively, resulting higher yields. Detecting disease using images is an intrinsically difficult task. In addition detection, individual species necessary for applying tailored control methods. A survey research initiatives that use convolutional neural networks (CNN), a type DL, address detection concerns was undertaken the current publication. this work, we reviewed 100 most relevant CNN articles on detecting leaf over last five years. addition, identified summarized several problems solutions corresponding used detection. Moreover, Deep (DCNN) trained image data were effective method early We expressed benefits drawbacks utilizing agriculture, discussed direction future developments