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Found 2 papers, 1 papers with code
Forest aboveground biomass estimation using GEDI and earth observation data through attention-based deep learning
AU-FC achieved intermediate R2 of 0. 64, RMSE of 44. 92 Mgha-1, and bias of -0. 56 Mg ha-1, outperforming RF but underperforming AU model using spatial information.
Arbitrarily large iterative tomographic reconstruction on multiple GPUs using the TIGRE toolbox
Tomographic image sizes keep increasing over time and while the GPUs that compute the tomographic reconstruction are also increasing in memory size, they are not doing so fast enough to reconstruct the largest datasets.
Distributed, Parallel, and Cluster Computing
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