no code implementations • 10 Sep 2020 • Ryne Roady, Tyler L. Hayes, Christopher Kanan
Supervised classification methods often assume that evaluation data is drawn from the same distribution as training data and that all classes are present for training.
1 code implementation • 14 Jun 2020 • Ryne Roady, Tyler L. Hayes, Hitesh Vaidya, Christopher Kanan
In this work, we introduce Stream-51, a new dataset for streaming classification consisting of temporally correlated images from 51 distinct object categories and additional evaluation classes outside of the training distribution to test novelty recognition.
no code implementations • 30 Oct 2019 • Ryne Roady, Tyler L. Hayes, Ronald Kemker, Ayesha Gonzales, Christopher Kanan
We found that input perturbation and temperature scaling yield the best performance on large scale datasets regardless of the feature space regularization strategy.