Trained Vanilla Models on Synthetic Permeability Fields, 101 Data Points
收藏DataCite Commons2025-07-04 更新2026-05-07 收录
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https://darus.uni-stuttgart.de/citation?persistentId=doi:10.18419/DARUS-5081
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资源简介：
Models are trained with [git: DDUNet] on 101 data points (dp).
Both, vanilla UNet and DDU-Net, can be applied directly end-to-end.
For inference follow the guidelines of <a href="https://github.com/JuliaPelzer/Heat-Plume-Prediction/tree/AllIn1/LGCNN/release25/">Heat Plume Prediction</a> to prepare raw data, then apply the models as described in [git: DDUNet].
Based on raw data from <a href="https://doi.org/10.18419/darus-5064">https://doi.org/10.18419/darus-5064</a>.
提供机构：
DaRUS
创建时间：
2025-05-21
