isic-challenge-2018

isic-challenge-2018

https://github.com/dataset-ninja/isic-challenge-2018

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (0.6%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

isic-challenge-2018

Basic Info
  • Host: GitHub
  • Owner: dataset-ninja
  • License: other
  • Language: Python
  • Default Branch: main
  • Size: 21.9 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed 7 months ago
Metadata Files
Readme License Citation

README.md

ISIC Challenge 2018: International Skin Imaging Collaboration Challenge 2018

ISIC Challenge 2018 is a dataset for instance segmentation, semantic segmentation, and object detection tasks.

Owner

  • Name: dataset-ninja
  • Login: dataset-ninja
  • Kind: organization

Citation (CITATION.md)

If you make use of the ISIC Challenge 2018 data, please cite the following reference:

```bibtex
[1] Noel Codella, Veronica Rotemberg, Philipp Tschandl, M. Emre Celebi, Stephen Dusza, David Gutman, Brian Helba, Aadi Kalloo, Konstantinos Liopyris, Michael Marchetti, Harald Kittler, Allan Halpern:
"Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)", 2018;
https://arxiv.org/abs/1902.03368

[2] Tschandl, P., Rosendahl, C. & Kittler, H.
The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.
Sci. Data 5, 180161 doi:10.1038/sdata.2018.161 (2018).
```

[Source](https://challenge.isic-archive.com/data/#2018)

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Dependencies

requirements.txt pypi