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physics.geo-ph2024
Fully invertible hyperbolic neural networks for segmenting large-scale surface and sub-surface data
Bas Peters, Eldad Haber, Keegan Lensink
The large spatial/temporal/frequency scale of geoscience and remote-sensing datasets causes memory issues when using convolutional neural networks for (sub-) surface data segmentat…
physics.geo-ph2020★ 3 cited
Fully reversible neural networks for large-scale surface and sub-surface characterization via remote sensing
Bas Peters, Eldad Haber, Keegan Lensink
The large spatial/frequency scale of hyperspectral and airborne magnetic and gravitational data causes memory issues when using convolutional neural networks for (sub-) surface cha…