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Image enhancement code: time-resolved tomograms of EICP application using 3D...
- b2find.dkrz.de
Updated Oct 23, 2023+ more versions
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EmailClick to copy linkLink copiedCite(2023). Image enhancement code: time-resolved tomograms of EICP application using 3D U-net - Dataset - B2FIND [Dataset]. https://b2find.dkrz.de/dataset/fc0a815a-4c82-5917-b727-4c149998b91aDataset updatedOct 23, 2023DescriptionThis dataset contains the codes to reproduce the results of "Time resolved micro-XRCT dataset of Enzymatically Induced Calcite Precipitation (EICP) in sintered glass bead columns", cf. https://doi.org/10.18419/darus-2227. The code takes "low-dose" images as an input where the images contain many artifacts and noise as a trade-off of a fast data acquisition (6 min / dataset while 3 hours / dataset ("high-dose") in normal configuration). These low quality images are able to be improved with the help of a pre-trained model. The pre-trained model provided in here is trained with pairs of "high-dose" and "low-dose" data of above mentioned EICP application. The examples of used training, input and output data can be also found in this dataset. Although we showed only limited examples in here, we would like to emphasize that the used workflow and codes can be further extended to general image enhancement applications. The code requires a Python version above 3.7.7 with packages such as tensorflow, kears, pandas, scipy, scikit, numpy and patchify libraries. For further details of operation, please refer to the readme.txt file.
- Z
API Database of Python frameworks & Labeled Issues
- data.niaid.nih.gov
- zenodo.org
Updated Aug 4, 2021ShareFacebookTwitterEmailClick to copy linkLink copiedCiteAnonymous Authors (2021). API Database of Python frameworks & Labeled Issues [Dataset]. https://data.niaid.nih.gov/resources?id=ZENODO_2756358Dataset updatedAug 4, 2021Dataset authored and provided byAnonymous AuthorsLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionPyLibAPIs.7z : contains public API data (mongodb dump) for these frameworks:
TensorFlow
Keras
scikit-learn
Pandas
Flask
Django
Label.xlsx: cintains issues and their labels
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FacebookTwitterEmailImage enhancement code: time-resolved tomograms of EICP application using 3D U-net - Dataset - B2FIND
This dataset contains the codes to reproduce the results of "Time resolved micro-XRCT dataset of Enzymatically Induced Calcite Precipitation (EICP) in sintered glass bead columns", cf. https://doi.org/10.18419/darus-2227. The code takes "low-dose" images as an input where the images contain many artifacts and noise as a trade-off of a fast data acquisition (6 min / dataset while 3 hours / dataset ("high-dose") in normal configuration). These low quality images are able to be improved with the help of a pre-trained model. The pre-trained model provided in here is trained with pairs of "high-dose" and "low-dose" data of above mentioned EICP application. The examples of used training, input and output data can be also found in this dataset. Although we showed only limited examples in here, we would like to emphasize that the used workflow and codes can be further extended to general image enhancement applications. The code requires a Python version above 3.7.7 with packages such as tensorflow, kears, pandas, scipy, scikit, numpy and patchify libraries. For further details of operation, please refer to the readme.txt file.