{"title":"基于卷积神经网络的螺栓松动检测技术研究进展","authors":"Zhenzhu Guo, Yiduo Zhang","doi":"10.1109/scset55041.2022.00059","DOIUrl":null,"url":null,"abstract":"Convolutional neural networks have powerful generalization and expression capabilities for extracting deep-level features of images. Their emergence has further promoted the development of artificial intelligence, and greatly improved the image recognition and detection effects and computer operating speed. With the advent of the global intelligent era, image recognition and detection technology based on convolutional neural networks has emerged in various fields of workpiece detection, and it has also brought challenges for professionals in this field to optimize intelligent algorithms. In this paper, the recognition process of the convolutional neural network and the current research status of the convolutional neural network in the recognition of bolt looseness images are described and prospected.","PeriodicalId":446933,"journal":{"name":"2022 International Seminar on Computer Science and Engineering Technology (SCSET)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Research Progress Of Bolt Loose Detection Technology Based On Convolutional Neural Network\",\"authors\":\"Zhenzhu Guo, Yiduo Zhang\",\"doi\":\"10.1109/scset55041.2022.00059\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Convolutional neural networks have powerful generalization and expression capabilities for extracting deep-level features of images. Their emergence has further promoted the development of artificial intelligence, and greatly improved the image recognition and detection effects and computer operating speed. With the advent of the global intelligent era, image recognition and detection technology based on convolutional neural networks has emerged in various fields of workpiece detection, and it has also brought challenges for professionals in this field to optimize intelligent algorithms. In this paper, the recognition process of the convolutional neural network and the current research status of the convolutional neural network in the recognition of bolt looseness images are described and prospected.\",\"PeriodicalId\":446933,\"journal\":{\"name\":\"2022 International Seminar on Computer Science and Engineering Technology (SCSET)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Seminar on Computer Science and Engineering Technology (SCSET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/scset55041.2022.00059\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Seminar on Computer Science and Engineering Technology (SCSET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/scset55041.2022.00059","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research Progress Of Bolt Loose Detection Technology Based On Convolutional Neural Network
Convolutional neural networks have powerful generalization and expression capabilities for extracting deep-level features of images. Their emergence has further promoted the development of artificial intelligence, and greatly improved the image recognition and detection effects and computer operating speed. With the advent of the global intelligent era, image recognition and detection technology based on convolutional neural networks has emerged in various fields of workpiece detection, and it has also brought challenges for professionals in this field to optimize intelligent algorithms. In this paper, the recognition process of the convolutional neural network and the current research status of the convolutional neural network in the recognition of bolt looseness images are described and prospected.