Intelligent detection of underground openings and surrounding disturbed zones

• Main Authors: Meng, Wenzhao, Wu, Wei, Poh, Teoh Yaw, Lim, Zhu Liang
• 其他作者: School of Civil and Environmental Engineering
• 格式: Article
• 語言: English
• 出版: 2025
• 主題: Engineering; Convolutional neural network; Data augmentation
• 在線閱讀: https://hdl.handle.net/10356/182702
• 機構: Nanyang Technological University

This study aims to develop an intelligent method to detect subsurface anomalies for prediction and mitigation of geologic risks. We trained a convolutional neural network (CNN) model using the seismic data from 6 field cases of regular pipes and irregular cavities and a sliding time window technique...