Applying textural Law’s masks to images using machine learning
Abdikerimova G. Yessenova M. Yerzhanova A. Manbetova Z. Murzabekova G. Kaibassova D. Bekbayeva R. Aldashova M.
October 2023Institute of Advanced Engineering and Science
International Journal of Electrical and Computer Engineering
2023#13Issue 55569 - 5575 pp.
Currently, artificial neural networks are experiencing a rebirth, which is primarily due to the increase in the computing power of modern computers and the emergence of very large training data sets available in global networks. The article considers Laws texture masks as weights for a machine-learning algorithm for clustering aerospace images. The use of Laws texture masks in machine learning can help in the analysis of the textural characteristics of objects in the image, which are further identified as pockets of weeds. When solving problems in applied areas, in particular in the field of agriculture, there are often problems associated with small sample sizes of images obtained from aerospace and unmanned aerial vehicles and insufficient quality of the source material for training. This determines the relevance of research and development of new methods and algorithms for classifying crop damage. The purpose of the work is to use the method of texture masks of Laws in machine learning for automated processing of high-resolution images in the case of small samples using the example of problems of segmentation and classification of the nature of damage to crops.
Image processing , k-means , Law’s textural masks , Machine learning , Texture analysis , Weeds
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Department of Information Systems, Faculty of Information Technology, L. N. Gumilyov Eurasian National University, Astana, Kazakhstan
Department of Technological Machines and Equipment, Faculty of Technology, S. Seifullin Кazakh Agrotechnical University, Astana, Kazakhstan
Department of Radio Engineering, Electronics and Telecommunications, Faculty of Energy, Saken Seifullin Kazakh Agrotechnical University, Astana, Kazakhstan
Department of Computer Sciences, Faculty of Information Technology, S. Seifullin Кazakh Agrotechnical University, Astana, Kazakhstan
Department of Information and Computing Systems, Non-Profit Limited Company Abylkas Saginov Karaganda State University, Karaganda, Kazakhstan
Department of Automation, Information Technology, Urban Development of Non-Profit Limited Company Semey University named after Shakarim, Semey, Kazakhstan
Department of Information Systems
Department of Technological Machines and Equipment
Department of Radio Engineering
Department of Computer Sciences
Department of Information and Computing Systems
Department of Automation
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