2023, Volume 7 Issue 4
A Review of Deep Learning for Detecting and Classifying Plant Disease
AUTHOR(S)
Nithin Kurian, Refin Reji Varghese, Akash C Mohan, Sebin Babu, Roji Thomas
DOI: https://doi.org/10.46647/ijetms.2023.v07i04.063
ABSTRACT
Artificial intelligence has a subfield called deep learning. Recent years have seen a significant increase in interest from both academic and commercial circles due to the benefits of autonomous learning and feature extraction. It has been extensively utilized in the processing of images, videos, voices, and natural languages. In addition, it has developed into a hub for research in agricultural plant protection, including the identification of plant diseases and the evaluation of pest ranges. The use of deep learning in the detection of plant diseases can prevent the drawbacks brought on by the artificial selection of disease spot traits, make the extraction of plant disease features more objective, and accelerate the pace of technological advancement. This paper details the development of deep learning technologies in recent years for the diagnosis of crop leaf diseases. Using deep learning and cutting-edge imaging techniques, we explain the current trends and difficulties in the identification of plant leaf disease in this study. We anticipate this work to be a useful tool for scientists looking into the identification of plant diseases and insect pests. At the same time, we also talked about some of the present difficulties and issues that must be tackled.
Page No: 479 - 484
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How to Cite This Article:
Nithin Kurian, Refin Reji Varghese, Akash C Mohan, Sebin Babu, Roji Thomas
. A Review of Deep Learning for Detecting and Classifying Plant Disease
. ijetms;7(4):479-484. DOI: 10.46647/ijetms.2023.v07i04.063