Identification of Underground Artificial Cavities Based on the Bayesian Convolutional Neural Network
Jigen Xia,
Ronghua Peng,
Zhiqiang Li
et al.
Abstract:The development of underground artificial cavities plays an important role in the exploitation of urban spatial resources. As the rapidly growing number of underground artificial cavities with different depths and scales increases, the detection and identification of underground artificial cavities has become a key issue in underground engineering studies. Geophysical techniques have been widely used for the construction, management, and maintenance of underground artificial cavities. In this study, we present… Show more
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