General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • E-mail:
    • Journal Metrics:

Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2020 Vol.12(5): 118-122 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2020.V12.1275

A Review on Deep Learning Based Image Classification of Plant Diseases

Praveen S. Muthukumarana and Achala C. Aponso

Abstract—A large portion of agricultural crop yield is lost due to plant diseases. The impact of this is more severe in developing countries that do not have sufficient trained professionals to identify and treat diseases. Deep learning has shown promising results in the field of image classification and is adopted in fields such as medicine. However, its' adoption in the field of agriculture has been slow in comparison. There are many examples in literature that had trained deep learning models to detect plant diseases by images. However, there is still no successful application developed that works in the real world. In this paper, the authors review the research efforts that have been done in the area of image-based plant disease detection with deep learning and try to analyze the challenges faced in adopting it in the agricultural sector. The authors examine datasets used, image pre-processing conducted and deep learning technologies utilized.

Index Terms—CNN, computer vision, disease classification, plant diseases, visible symptoms, automatic identification.

Praveen S. Muthukumarana and Achala C. Aponso are with Informatics Institute of Technology, Colombo, Sri Lanka (e-mail:,


Cite:Praveen S. Muthukumarana and Achala C. Aponso, "A Review on Deep Learning Based Image Classification of Plant Diseases," International Journal of Computer Theory and Engineering vol. 12, no. 5, pp. 118-122, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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