Automated detection of ferromagnetic pipelines from magnetic total-field anomaly data using convolutional neural networks
Author:
Affiliation:
1. Colorado School of Mines
2. U.S. Department of Energy
Publisher
Society of Exploration Geophysicists and American Association of Petroleum Geologists
Link
https://library.seg.org/doi/pdf/10.1190/image2023-3912400.1
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4. Milletari, F., N. Navab, and S.A. Ahmadi, 2016, V-net: Fully convolutional neural networks for volumetric medical image segmentation: Fourth International Conference on 3D Vision (3DV), doi: 10.1109/3DV.2016.79.
5. Toward a three‐dimensional automatic interpretation of potential field data via generalized Hilbert transforms: Fundamental relations
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