A deep learning framework based on improved self-supervised learning for ground-penetrating radar tunnel lining inspection

It is not practical to obtain a large number of labeled data to train a supervised learning network in tunnel lining nondestructive testing with ground-penetrating radar (GPR). To decrease the dependence of supervised learning on the number of labeled data, an improved self-supervised learning algorithm—self-attention dense contrastive...

Marchenko inversion of gpr data for a 1d dissipative medium

Radar data collected on two sides of a horizontally dissipative layered medium are required to invert for the medium parameters. The two-sided reflection and transmission responses are reduced to two single-sided reflection responses. One is the measured dissipative medium response, and the other is the reflection response of the...