science_cases:iwf_science_case
Differences
This shows you the differences between two versions of the page.
Both sides previous revisionPrevious revisionNext revision | Previous revision | ||
science_cases:iwf_science_case [2022/09/12 13:00] – old revision restored (2022/09/12 12:59) admin | science_cases:iwf_science_case [2022/09/12 13:06] (current) – admin | ||
---|---|---|---|
Line 27: | Line 27: | ||
Starting from the reimplementation, | Starting from the reimplementation, | ||
- | We proposed a pipeline using a **UNet ** (Ronneberger et al., 2015) including residual blocks, squeeze and excitation blocks, Atrous Spatial Pyramidal Pooling (ASPP) and attention blocks, similar to the **ResUNet** (Jha et al., 2019), for the automatic detection of ICMEs. Comparing it to our first results, we find that our model outperforms the baseline regarding GPU usage, training time and robustness to missing [[: | + | We proposed a pipeline using a **UNet ** (Ronneberger et al., 2015) including residual blocks, squeeze and excitation blocks, Atrous Spatial Pyramidal Pooling (ASPP) and attention blocks, similar to the **< |
Results of this science case were presented at the {{: | Results of this science case were presented at the {{: |
science_cases/iwf_science_case.1662980423.txt.gz · Last modified: 2022/09/12 13:00 by admin