1 code implementation • 27 Apr 2022 • Ilke Cugu, Massimiliano Mancini, Yanbei Chen, Zeynep Akata
Generalizing visual recognition models trained on a single distribution to unseen input distributions (i. e. domains) requires making them robust to superfluous correlations in the training set.
1 code implementation • 4 Feb 2021 • Ilke Cugu, Emre Akbas
Convolutional neural networks (CNNs) are able to attain better visual recognition performance than fully connected neural networks despite having much fewer parameters due to their parameter sharing principle.