Intelligent detection of underground openings and surrounding disturbed zones

• المؤلفون الرئيسيون: Meng, Wenzhao, Wu, Wei, Poh, Teoh Yaw, Lim, Zhu Liang
• مؤلفون آخرون: School of Civil and Environmental Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2025
• الموضوعات: Engineering; Convolutional neural network; Data augmentation
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/182702

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...