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201 to 210 of 265 Results
README.md
Nov 20, 2025 - Jose et al. MLST 2025 - Code, Data and Models
Markdown Text - 7.1 KB - MD5: ec57a35fa6827ff4c7ec8ccefd1ad741
README_TR.md
Nov 20, 2025 - Jose et al. MLST 2025 - Code, Data and Models
Markdown Text - 4.2 KB - MD5: 20d20face9a008611f9d0f5194a1a6e1
SynDataGenerator.py
Nov 20, 2025 - Jose et al. MLST 2025 - Code, Data and Models
Python Source Code - 64.2 KB - MD5: d95b3272410a78a370276ccf9fd13bd6
SynValDataGenerator.py
Nov 20, 2025 - Jose et al. MLST 2025 - Code, Data and Models
Python Source Code - 17.8 KB - MD5: 7143ea88c0658494aced5641264cb76c
train_config_soot_r50.py
Nov 20, 2025 - Jose et al. MLST 2025 - Code, Data and Models
Python Source Code - 5.0 KB - MD5: 18e27367ab1fd5363bf71c8913ad3daa
train_net_main.py
Nov 20, 2025 - Jose et al. MLST 2025 - Code, Data and Models
Python Source Code - 7.5 KB - MD5: 597aec6f6fcd41ee1d08711b95c247c1
validation_soot_piv_5.tar
Nov 20, 2025 - Jose et al. MLST 2025 - Code, Data and Models
TAR Archive - 173.9 MB - MD5: dd715182ded0158dc0de86c2a94aaeed
Code for training and using the soot (instance) segmentation models
Oct 31, 2025 - Soot segmentation
Jose, Basil; Geigle, Klaus Peter; Hampp, Fabian, 2025, "Code for training and using the soot (instance) segmentation models", https://doi.org/10.18419/DARUS-5184, DaRUS, V2
This dataset contains the necessary code for using our soot (instance) segmentation model used for segmenting soot filaments from PIV (Mie scattering) images. In the corresponding paper, an ablation study is conducted to delineate the effects of domain randomisation parameters of synthetically generated training data on the segmentation accuracy. T...
README.md
Oct 31, 2025 - Code for training and using the soot (instance) segmentation models
Markdown Text - 2.8 KB - MD5: ee22fe0f3e520725023de5dc340abf0c
soot_inference.py
Oct 31, 2025 - Code for training and using the soot (instance) segmentation models
Python Source Code - 2.9 KB - MD5: 6970ec34453420a834c798809b0d402c
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