CIFAR-10H (also referred to as CIFAR10H) is an accompanying human
label dataset for the 10,000-image test set of CIFAR-10,
originally created as a new benchmark for object classification:

    Peterson, J.*, Battleday, R.*, Griffiths, T., & Russakovsky, O. (2019). 
    Human uncertainty makes classification more robust.
    In Proceedings of the IEEE International Conference on Computer Vision.
    * equal contribution
    
It is the joint creation of Joshua C. Peterson and Ruairidh M. Battleday,
under the advisorship of Thomas L. Griffiths and Olga Russakovsky.

The CIFAR-10H dataset (including any metadata, scripts, and
documentation) is made available under Creative Commons BY-NC-SA 4.0 license.
You can use, redistribute, and adapt it for non-commercial purposes, 
as long as you (a) give appropriate credit by citing our paper, 
(b) indicate any changes that you've made, and
(c) distribute any derivative works under the same license.

    https://creativecommons.org/licenses/by-nc-sa/4.0/
    
The CIFAR-10 image and original label data can be found at:
https://www.cs.toronto.edu/~kriz/cifar.html
