首页> Structural health monitoring> Deep learning-based concrete defects classification and detection using semantic segmentation.

Deep learning-based concrete defects classification and detection using semantic segmentation.

导出 LinkOut

翻译打印收藏纠错

第一作者： Palisa,Arafin

第一单位： Department of Civil Engineering, Lakehead University, Thunder Bay, ON, Canada.

作者： Palisa,Arafin ^[1] ; Ahm Muntasir,Billah ^[2] ; Anas,Issa ^[3]

作者单位： Department of Civil Engineering, Lakehead University, Thunder Bay, ON, Canada. ^[1] Department of Civil Engineering, University of Calgary, Calgary, AB, Canada. ^[2] Department of Civil and Environmental Engineering, United Arab Emirates University, Al Ain, Abu Dhabi, UAE. ^[3]

关键词 Concrete defects convolutional neural network encoder-decoder model semantic segmentation structural health monitoring

DOI 10.1177/14759217231168212

PMID 38078049

发布时间 2023-12-11

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交

浏览0

Structural health monitoring

2024年23卷1期

383-409页

相似文献

中文期刊
外文期刊
学位论文
会议论文

浏览0

点击下载本期目录封面

Structural health monitoring

2024年23卷1期

383-409页

检索历史清除

Deep learning-based concrete defects classification and detection using semantic segmentation.

Structural health monitoring

相似文献

同项目论文

Structural health monitoring

相关期刊

参考文献：
指定格式：	NoteExpress EndNote RefWorks NoteFirst

检索历史 清除

Deep learning-based concrete defects classification and detection using semantic segmentation.

Structural health monitoring

相似文献

同项目论文

Structural health monitoring

相关期刊

检索历史清除