Learning from clutter: an unsupervised learning-based clutter removal scheme for GPR B-scans
Ground-penetrating radar (GPR) data are often contaminated by hardware and environmental clutter, which significantly affects the accuracy and reliability of target response identification. Existing supervised deep learning techniques for removing clutter in GPR data require generating a large set o...
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Main Authors: | , , , , , , |
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格式: | Article |
語言: | English |
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2025
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在線閱讀: | https://hdl.handle.net/10356/182188 |
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機構: | Nanyang Technological University |
語言: | English |