Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

BigEarthNet: Large-Scale Sentinel-2 Benchmark 66GB #23

Open
andreaschandra opened this issue Apr 20, 2021 · 0 comments
Open

BigEarthNet: Large-Scale Sentinel-2 Benchmark 66GB #23

andreaschandra opened this issue Apr 20, 2021 · 0 comments
Assignees
@juannat7
Labels
good first issue Good for newcomers priority: high essential things type: feature work: complex

Comments

@andreaschandra
Copy link
Member

andreaschandra commented Apr 20, 2021 •
edited
Loading

Add scene classification dataset, similar to image classification
https://github.com/chrieke/awesome-satellite-imagery-datasets#4-scene-classification-chipimage-recognition

  • BigEarthNet: Large-Scale Sentinel-2 Benchmark 66GB (TU Berlin, Jan 2019)
    Multiple landcover labels per chip based on CORINE Land Cover (CLC) 2018, 590,326 chips from Sentinel-2 L2A scenes (125 Sentinel-2 tiles from 10 European countries, 2017/2018), 66 GB archive, Paper: Sumbul et al. 2019
@andreaschandra andreaschandra added enhancement New feature or request good first issue Good for newcomers priority: high essential things type: feature work: complex labels Apr 20, 2021
@andreaschandra andreaschandra removed the enhancement New feature or request label Apr 25, 2021
@andreaschandra andreaschandra changed the title Scene Classification Dataset BigEarthNet: Large-Scale Sentinel-2 Benchmark 66GB Apr 25, 2021
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees

@juannat7 juannat7

Labels
good first issue Good for newcomers priority: high essential things type: feature work: complex
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
2 participants
@andreaschandra @juannat7