O. Sheremet, O. Kovalchuk, Kateryna Sheremet, O. Sadovoi, T. Kiriienko, Yuliia Sokhina
{"title":"Computer Vision System for Determining the Reference Point","authors":"O. Sheremet, O. Kovalchuk, Kateryna Sheremet, O. Sadovoi, T. Kiriienko, Yuliia Sokhina","doi":"10.1109/KhPIWeek57572.2022.9916417","DOIUrl":null,"url":null,"abstract":"The stages of development and implementation of neural network methods for visual determination of the reference points coordinates of a specific technical object are considered. Publicly available information about artificial neural networks and computer vision is analyzed. The description of the proposed intellectual system is carried out, questions of data markup, as well as an artificial increase in their number, are raised. The resulting intelligent system has an average accuracy of 95.2%.","PeriodicalId":197096,"journal":{"name":"2022 IEEE 3rd KhPI Week on Advanced Technology (KhPIWeek)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 3rd KhPI Week on Advanced Technology (KhPIWeek)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KhPIWeek57572.2022.9916417","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The stages of development and implementation of neural network methods for visual determination of the reference points coordinates of a specific technical object are considered. Publicly available information about artificial neural networks and computer vision is analyzed. The description of the proposed intellectual system is carried out, questions of data markup, as well as an artificial increase in their number, are raised. The resulting intelligent system has an average accuracy of 95.2%.