Omkar2118/datasets huggingface dataset:
Carbon Intensity 2020
Full name: Carbon Intensity Data of Germany, Great Britain, France, and California in 2020

Energy production and carbon intensity datasets for the regions Germany, Great Britain, France (all via the [ENTSO-E Transparency Platform](https://transparency.entsoe.eu/)) and California (via [California ISO](https://www.caiso.com/)) for the entire year 2020 +-10 days.

Introducing paper: Let's Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud
SMLM CEP152-Complex FITS Images
Full name: SMLM CEP152-Complex FITS Images

The following files comprise 19 sets of 40,000 images, each set corresponding to a different rendering sigma as described in the paper.

* Extracting *

To extract the files, execute the following command (under Linux):

cat paper_data.tar.gz.* | tar xzvf -

 

* Organisation *

The data are grouped into 19 directories, corresponding to the sigma value they were rendered at. These values are

10, 9, 8.1,  7.29, 6.56, 5.9, 5.31, 4.78, 4.3, 3.87, 3.65, 3.28, 2.95, 2.66, 2.39, 2.15, 1.94, 1.743, 1.57, 1.41

Each directory contains 40,000 FITS files - a NASA floating point image standard. The images are single channel and un-normalised. This structure is ready to be used

* Recreating the data *

If you have the time and compute power, you can regenerate this data set with as many or as few images as you prefer, at any sigma level. The original experimental data is available at <fill in later>.

To recreate the data set you need to download the CEPRender program, available on github: https://github.com/OniDaito/CEPrender - details on how to use this program are available with the code.

Introducing paper: 3D Structure from 2D Microscopy images using Deep Learning