{"title":"Corrigendum to CrackDenseLinkNet: a deep convolutional neural network for semantic segmentation of cracks on concrete surface images","authors":"","doi":"10.1177/14759217231199536","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":51184,"journal":{"name":"Structural Health Monitoring-An International Journal","volume":" ","pages":""},"PeriodicalIF":5.7000,"publicationDate":"2023-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structural Health Monitoring-An International Journal","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/14759217231199536","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
期刊介绍：
Structural Health Monitoring is an international peer reviewed journal that publishes the highest quality original research that contain theoretical, analytical, and experimental investigations that advance the body of knowledge and its application in the discipline of structural health monitoring.
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