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Found 4 papers, 1 papers with code
Uncertainty-enabled machine learning for emulation of regional sea-level change caused by the Antarctic Ice Sheet
Projecting sea-level change in various climate-change scenarios typically involves running forward simulations of the Earth's gravitational, rotational and deformational (GRD) response to ice mass change, which requires high computational cost and time.
Reconstructing Cardiac Electrical Excitations from Optical Mapping Recordings
That the inclusion of explicit modeling information has negligible to negative effects on the reconstruction implies the need for new avenues for optimization of data assimilation schemes applied to cardiac electrical excitation.
AeroRIT: A New Scene for Hyperspectral Image Analysis
We investigate applying convolutional neural network (CNN) architecture to facilitate aerial hyperspectral scene understanding and present a new hyperspectral dataset-AeroRIT-that is large enough for CNN training.
Tracking in Aerial Hyperspectral Videos using Deep Kernelized Correlation Filters
Hyperspectral imaging holds enormous potential to improve the state-of-the-art in aerial vehicle tracking with low spatial and temporal resolutions.
