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[P] CIFAR-10H – Human guess distribution soft labels for CIFAR-10 (Dataset Release)

CIFAR-10H is a new dataset of soft labels reflecting human perceptual uncertainty for the 10,000-image CIFAR-10 test set, which we are releasing today. It first appears in the paper:

Joshua C. Peterson, Ruairidh M. Battleday, Thomas L. Griffiths, & Olga Russakovsky (2019). Human uncertainty makes classification more robust. In Proceedings of the IEEE International Conference on Computer Vision. https://arxiv.org/abs/1908.07086

Dataset Link: https://github.com/jcpeterson/cifar-10h/

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.