Simulation of GPR B-Scan Data Based on Dense Generative Adversarial Network

Urban subsurface infrastructures, e.g., pipelines and roads, are aging with the expansion of modern cities. Benefiting from the capability of nondestructive detection, ground penetrating radar (GPR) has been widely applied to underground objects or disasters detection, and GPR B-scan images are empl...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing 2023-01, Vol.16, p.1-7
Hauptverfasser:	Wang, Bin, Chen, Peiyao, Zhang, Gong
Format:	Artikel
Sprache:	eng
Schlagworte:	Ablation Automation Buried object detection Computer networks Convolution Data augmentation Data simulation Detection Disasters Feature extraction generative adversarial network generative adversarial network (GAN) Generative adversarial networks Generators Ground penetrating radar ground penetrating radar (GPR) Image edge detection Radar Radar detection Regularization Simulation Synthetic data Training Urban areas weighted total variation weighted total variation (w-TV)
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