METHOD OF ARTIFICIAL INTELLIGENCE IN IDENTIFICATION OF PLANT DISEASES

Dalipi, Zani and Shaini, Bilall and Ahmeti, Fisnik and Rexhepi, Shpetim (2024) METHOD OF ARTIFICIAL INTELLIGENCE IN IDENTIFICATION OF PLANT DISEASES. JNSM Journal of Natural Sciences and Mathematics of UT, 9 (17-18). pp. 407-428. ISSN 2671-3039

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Abstract

In this paper, we explain the influence of modern technology in the identification of plant diseases. The best way nowadays to solve this problem is to use some artificial intelligence methodologies. Still, in particular, we will train Machine Learning as a field that deals with the detection of plant diseases. In this paper, we will talk about the basic principles of how artificial intelligence can be practical in agriculture, to select some problems that were once not possible due to the lack of development of technology or the lack of scientific knowledge. Through this work, a software developer can get basic knowledge to develop software or applications that will be able to identify plant diseases. The work includes the methodology of how plant diseases can be identified through any application. Our contribution is for all developers who are interested in developing technology in the field of agriculture, for this reason, we have explained the concepts of artificial intelligence and software development methodologies. Readers can have a clear overview of technology development in the agricultural sector.

Item Type:	Article
Uncontrolled Keywords:	Artificial intelligence, Software in agriculture, Transfer-learning, CNN architecture, Optimizing weights.
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Engineering, Science and Mathematics > School of Mathematics
Depositing User:	Unnamed user with email zshi@unite.edu.mk
Date Deposited:	26 Dec 2024 13:50
Last Modified:	26 Dec 2024 13:50
URI:	http://eprints.unite.edu.mk/id/eprint/1971

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