Using deep learning algorithms to classify crop diseases
Murzabekova G. Glazyrina N. Nekessova A. Ismailova A. Bazarova M. Kashkimbayeva N. Mukhametzhanova B. Aldashova M.
December 2023Institute of Advanced Engineering and Science
International Journal of Electrical and Computer Engineering
2023#13Issue 66737 - 6744 pp.
The use of deep learning algorithms for the classification of crop diseases is one of the promising areas in agricultural technology. This is due to the need for rapid and accurate detection of plant diseases, which allows timely measures to be taken to treat them and prevent their spread. One of them is to increase productivity and maintain land quality through the timely detection of diseases and pests in agriculture and their elimination. Traditional classification methods in machine learning and algorithms in deep learning were compared to note the high accuracy in detecting pests and crop diseases. The advantages and disadvantages of each model considered during training were taken into account, and the Inception V3 algorithm was incorporated into the application. They can monitor the condition of crops on a daily basis with the help of new technology-applications on gadgets. Aerial photographs used by research institutes and agricultural grain centers do not show the changes that occur in agricultural grains, that is, diseases and pests. Therefore, the method proposed in this paper determines the types of diseases and pests of cereals through a mobile application and suggests ways to deal with them.
Classification , Clustering , Deep learning , Image processing , Machine learning , Plant diseases
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Department of Computer Sciences, S. Seifullin Кazakh Agrotechnical University, Astana, Kazakhstan
Department of Computer and Software Engineering, L. N. Gumilyov Eurasian National University, Astana, Kazakhstan
Department of Information Systems, L. N. Gumilyov Eurasian National University, Astana, Kazakhstan
Department of Information Systems, S. Seifullin Кazakh Agrotechnical University, Astana, Kazakhstan
Higher School of IT and Natural Sciences, the East Kazakhstan University. S. Amanzholova, Ust-Kamenogorsk, Kazakhstan
Department of Information and Computing System, Abylkas Saginov Karaganda Technical University, Karaganda, Kazakhstan
Department of Computer Sciences
Department of Computer and Software Engineering
Department of Information Systems
Department of Information Systems
Higher School of IT and Natural Sciences
Department of Information and Computing System
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