3 ms·

> The state of the art is currently at about 80% classification accuracy 13 years later, I guess it's around 99% accuracy. https://en.wikipedia.org/wiki/CIFAR

• gcr 3y ago
  Top papers claim 99.5% accuracy. Since this is measured on a 10,000-sample evaluation set, there are 50 misclassified results. I'd love to see a table of them. Back in the day, papers claiming top performance on MNIST would just start to enumerate all of the misclassified test samples, e.g. https://www.researchgate.net/figure/All-of-the-misclassified-MNIST-test-digits-using-our-method-63-out-of-10-000-The-text_fig4_2528210 https://www.researchgate.net/figure/All-of-the-misclassified... from 2002. Newer papers have whittled this down to five misclassified digits, e.g. see §4.4 from https://arxiv.org/pdf/2001.09136v6.pdf https://arxiv.org/pdf/2001.09136v6.pdf for this particular flourish, though this isn't quite standard protocol (sample is counted as correct if any models in the ensemble match, not the majority)