Dataset for "MicrographCleaner: A python package for cryo-EM micrograph cleaning using deep learning"
<div></div> <div><a href="https://zenodo.org/api/records/17093439/draft/files/micrographCleaner_dataset.tar.gz/content" target="_blank" rel="noopener noreferrer">micrographCleaner_dataset.tar.gz</a>: </div> <p>The dataset used for the Publicaton "MicrographCleaner: A python package for cryo-EM micrograph cleaning using deep learning" <a href="https://doi.org/10.1016/j.jsb.2020.107498">https://doi.org/10.1016/j.jsb.2020.107498</a></p> <div> </div> <div></div> <div><a href="https://zenodo.org/api/records/17093439/draft/files/deepMicrographCleaner.tgz/content" target="_blank" rel="noopener noreferrer">deepMicrographCleaner.tgz</a>: the tensorflow-2-compatible model checkpoint</div> <p> </p>
ShareScore
28/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 0
- Engagement
- 0
Dataset details
- Repository
- zenodo
- Published
- May 31, 2020
- License
- cc-by-4.0
- DOI
- 10.5281/zenodo.6862670
Scored with release 0.9.0
ScienceDex for faculty
Your academic CV and NIH biosketch
Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.