K-STEMIT reduces RMSE by 21% for subsurface stratigraphy thickness estimation from radar data via a knowledge-informed spatio-temporal GNN with adaptive feature fusion and physical priors from the MAR weather model.
Deep hybrid wavelet network for ice boundary detection in radra imagery, in: IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, pp
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A beam steering method using an additional element achieves better than 5 μrad and 5 μm precision with >89.8% fiber-to-fiber coupling efficiency stable over 10-40°C temperature range.
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K-STEMIT: Knowledge-Informed Spatio-Temporal Efficient Multi-Branch Graph Neural Network for Subsurface Stratigraphy Thickness Estimation from Radar Data
K-STEMIT reduces RMSE by 21% for subsurface stratigraphy thickness estimation from radar data via a knowledge-informed spatio-temporal GNN with adaptive feature fusion and physical priors from the MAR weather model.
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Precise and robust optical beam steering for space optical instrumentation
A beam steering method using an additional element achieves better than 5 μrad and 5 μm precision with >89.8% fiber-to-fiber coupling efficiency stable over 10-40°C temperature range.