Plant Disease Detection Using Deep Learning Algorithms: A Systematic Review

Muhammad Faizan Zeb; Ghassan Husnain; Waqas Ahmad; Mohsin Tahir

Author(s)

Muhammad Faizan Zeb Department of Computer Science, IQRA National University,Peshawar, 25100,Pakistan

Ghassan Husnain Department of Computer Science, IQRA National University,Peshawar, 25100,Pakistan

Waqas Ahmad Department of Computer Science, IQRA National University,Peshawar, 25100,Pakistan

Mohsin Tahir Department of Electrical Engineering, IQRA National University,Peshawar,25100,Pakistan

Abstract

Plant diseases may have a considerable influence on crop yield and food security. The impact of plant diseases on agricultural output and food security is debatable. Therefore, for effective treatment and prevention of many diseases, early detection and identification are crucial. Recently, deep learning algorithms have drawn increased interest as a means of developing automated plant disease detection systems. This article provides a review of neural network techniques for image data processing, With an emphasis on crop disease detection. It gives a general summary of the data collection methods, deep learning models and architectures, and different image processing methods applied to the analysis of imaging data. This survey aims to facilitate future research in enhancing the system performance and accuracy of deep learning-based plant disease detection, by exploring its potential capabilities.

Publication Details

Page(s) 30-43

DOI DOI not available

Published Journal: The Sciencetech, Volume: 4, Issue: 2, Year: 2023

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Keywords

CNN, Neural Network, Plant disease, deep learning

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