Self-challenging improves cross-domain generalization
Abstract Convolutional Neural Networks (CNN) conduct image classification by activating
dominant features that correlated with labels. When the training and testing data are under …
dominant features that correlated with labels. When the training and testing data are under …
Self-Challenging Improves Cross-Domain Generalization
Z Huang, H Wang, EP Xing, D Huang - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
Abstract Convolutional Neural Networks (CNN) conduct image classification by activating
dominant features that correlated with labels. When the training and testing data are under …
dominant features that correlated with labels. When the training and testing data are under …
Self-Challenging Improves Cross-Domain Generalization
Z Huang, H Wang, EP Xing, D Huang - arXiv preprint arXiv:2007.02454, 2020 - arxiv.org
Convolutional Neural Networks (CNN) conduct image classification by activating dominant
features that correlated with labels. When the training and testing data are under similar …
features that correlated with labels. When the training and testing data are under similar …
Self-challenging Improves Cross-Domain Generalization
Z Huang, H Wang, EP Xing… - … European Conference on …, 2020 - experts.illinois.edu
Abstract Convolutional Neural Networks (CNN) conduct image classification by activating
dominant features that correlated with labels. When the training and testing data are under …
dominant features that correlated with labels. When the training and testing data are under …
Self-challenging Improves Cross-Domain Generalization
Z Huang, H Wang, EP Xing, D Huang - European Conference on …, 2020 - dl.acm.org
Abstract Convolutional Neural Networks (CNN) conduct image classification by activating
dominant features that correlated with labels. When the training and testing data are under …
dominant features that correlated with labels. When the training and testing data are under …
[PDF][PDF] Self-Challenging Improves Cross-Domain Generalization
Z Huang, H Wang, EP Xing, D Huang - arXiv preprint arXiv:2007.02454, 2020 - cs.cmu.edu
Convolutional Neural Networks (CNN) conduct image classification by activating dominant
features that correlated with labels. When the training and testing data are under similar …
features that correlated with labels. When the training and testing data are under similar …
[PDF][PDF] Self-Challenging Improves Cross-Domain Generalization
Z Huang, H Wang, EP Xing, D Huang - ri.cmu.edu
Convolutional Neural Networks (CNN) conduct image classification by activating dominant
features that correlated with labels. When the training and testing data are under similar …
features that correlated with labels. When the training and testing data are under similar …
[PDF][PDF] Self-Challenging Improves Cross-Domain Generalization
Z Huang, H Wang, EP Xing… - arXiv preprint arXiv …, 2020 - researchgate.net
Convolutional Neural Networks (CNN) conduct image classification by activating dominant
features that correlated with labels. When the training and testing data are under similar …
features that correlated with labels. When the training and testing data are under similar …
[PDF][PDF] Self-Challenging Improves Cross-Domain Generalization
Z Huang, H Wang, EP Xing, D Huang - ecva.net
Convolutional Neural Networks (CNN) conduct image classification by activating dominant
features that correlated with labels. When the training and testing data are under similar …
features that correlated with labels. When the training and testing data are under similar …
[PDF][PDF] Self-Challenging Improves Cross-Domain Generalization
Z Huang, H Wang, EP Xing, D Huang - arXiv preprint arXiv:2007.02454, 2020 - cs.cmu.edu
Convolutional Neural Networks (CNN) conduct image classification by activating dominant
features that correlated with labels. When the training and testing data are under similar …
features that correlated with labels. When the training and testing data are under similar …