[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117858-en":3,"doc-seo-117858-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117858,34359740700684,"Finn","https://ap-avatar.wpscdn.com/avatar/1f400023980c374ae676?_k=1777273430885731487",6,"Technology","Applying textural Law’s masks to images using machine learning","Artificial neural networks are gaining renewed attention due to increased computing power and access to large training datasets. The work applies Laws texture masks as weights in a machine-learning algorithm for clustering aerospace images. Using these texture masks supports analysis of image texture characteristics, enabling identification of weed pockets. Research addresses agriculture problems with small sample sizes from aerospace/UAV images and limited training data quality, aiming at automated segmentation and classification of crop damage.","Applying textural Law’s masks to images using machine  \nlearning  \nGulzira Abdikerimova1, Moldir Yessenova1, Akbota Yerzhanova2, Zhanat Manbetova3, Gulden Murzabekova4, Dinara Kaibassova5, Roza Bekbayeva6, Madina Aldashova1  \n1Department of Information Systems, Faculty of Information Technology, L. N. Gumilyov Eurasian National University, Astana,  \nRepublic of Kazakhstan  \n2Department of Technological Machines and Equipment, Faculty of Technology, S. Seifullin Кazakh Agrotechnical University, Astana,  \nRepublic of Kazakhstan  \n3Department of Radio Engineering, Electronics and Telecommunications, Faculty of Energy, Saken Seifullin Kazakh Agrotechnical  \nUniversity, Astana, Republic of Kazakhstan  \n4Department of Computer Sciences, Faculty of Information Technology, S. Seifullin Кazakh Agrotechnical University, Astana,  \nRepublic of Kazakhstan  \n5Department of Information and Computing Systems, Non-Profit Limited Company Abylkas Saginov Karaganda State University,  \nKaraganda, Republic of Kazakhstan  \n6Department of Automation, Information Technology and Urban Development of Non-Profit Limited Company Semey University  \nnamed after Shakarim, Semey, Republic of Kazakhstan  \n\n| Article history:\u003Cbr>Received Mar 1, 2023 Revised Apr 25, 2023 Accepted Apr 27, 2023 | 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 machinelearning 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 highresolution images in the case of small samples using the example of problems of segmentation and classification of the nature of damage to crops.\u003Cbr>This is an open access article under the CC BY-SA license.\u003Cbr> |\n| --- | --- |\n| Keywords:\u003Cbr>Image processing k-means\u003Cbr>Law’s textural masks Machine learning Texture analysis Weeds |  |\n\nCorresponding Author:  \nMoldir Yessenova  \nDepartment of Information Systems, Faculty Information Technology, L. N. Gumilyov Eurasian National University  \n010000 Astana, Republic of Kazakhstan [Email: moldir_11.92@mail.ru](Email: moldir_11.92@mail.ru)  \nArticle Info ABSTRACT  \n1. INTRODUCTION  \nIn the context of the globalization of economic mechanisms in agriculture, the role of food programs is increasing, aimed at solving the problems of providing the population with food, light, and food industrieswith raw materials. In developed countries, commercial agriculture predominates, while traditional forms of agriculture are represented mainly in developing countries. One of the main objectives ofthe program and plan is the development of the National Agriculture of the Republic of Kazakhstan, increasing the productivity, quality, and sustainability of agricultural products using modern technologies. The successful solution to such  \na problem requires automated image processing [1]–[4] for agricultural management, which can become a tool for displaying the state and structure of agricultural production and the results of the agricultural inventory. In addition, data reflecting the composition, structure, and state of agriculture in digital form are insufficiently presented. The solution to this problem requires the developmen","cbCaiuGVjNSLb8e5","https://ap.wps.com/l/cbCaiuGVjNSLb8e5","pdf",712185,1,7,"English","en",105,"# Abstract\n# Introduction\n## Motivation in agricultural image processing\n## Machine learning methods and remote sensing preprocessing\n## Prior work and research gap","[{\"question\":\"Why are Laws texture masks used in the proposed approach?\",\"answer\":\"Laws texture masks are used as weights in a machine-learning algorithm to capture and analyze textural characteristics in images, which helps identify vegetation-related damage regions.\"},{\"question\":\"What data and problem setting does the study target?\",\"answer\":\"The study targets high-resolution aerospace/UAV images where sample sizes are small and the source material quality for training is limited, affecting reliable segmentation and classification of crop damage.\"},{\"question\":\"How are clustering and preprocessing handled in the method?\",\"answer\":\"Remote sensing data preprocessing is used, the Laws texture mask method generates features as weights for machine learning, and k-means clustering is employed for grouping image regions.\"}]","Applying textural Law’s masks to images using machine learning | PDF",1785680025,18,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"applying-textural-laws-masks-to-images-using-machine-learning","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/technology/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/applying-textural-laws-masks-to-images-using-machine-learning/117858/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why are Laws texture masks used in the proposed approach?","Question",{"text":75,"@type":76},"Laws texture masks are used as weights in a machine-learning algorithm to capture and analyze textural characteristics in images, which helps identify vegetation-related damage regions.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What data and problem setting does the study target?",{"text":80,"@type":76},"The study targets high-resolution aerospace/UAV images where sample sizes are small and the source material quality for training is limited, affecting reliable segmentation and classification of crop damage.",{"name":82,"@type":73,"acceptedAnswer":83},"How are clustering and preprocessing handled in the method?",{"text":84,"@type":76},"Remote sensing data preprocessing is used, the Laws texture mask method generates features as weights for machine learning, and k-means clustering is employed for grouping image regions.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,113,117,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":111,"slug":112},50,"technology",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":114,"show_sort_weight":115,"slug":116},"Healthcare",40,"healthcare",{"id":118,"doc_module":4,"doc_module_name":46,"category_name":119,"show_sort_weight":120,"slug":121},8,"Research & Report",30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]