山东大学教师主页蒋鹏 Arbitrarily-oriented tunnel lining defects detection from Ground Penetrating Radar images using deep Convolutional Neural networks 中文主页

Arbitrarily-oriented tunnel lining defects detection from Ground Penetrating Radar images using deep Convolutional Neural networks: 发布时间：2024-10-01 | 点击次数：

所属单位：控制科学与工程学院

发表刊物：Automation in Construction

关键字：Arbitrarily-oriented defect detection;Automation;Deep learning;Ground penetrating radar;Tunnel inspection

第一作者：王静

论文编号：1523583211215523842

卷号：133

字数：50

是否译文：否

发表时间：2021-11

上一条： An extreme gradient boosting technique to estimate TBM penetration rate and prediction platform

下一条： Unsupervised Deep Learning for Random Noise Attenuation of Seismic Data