Funder
Ministry of Science, ICT and Future Planning
National Research Foundation of Korea
Institute for Information and Communications Technology Promotion
Subject
Computer Vision and Pattern Recognition,Signal Processing,Software
Reference50 articles.
1. Augustin, M., Meinke, A., Hein, M., 2020. Adversarial robustness on in-and out-distribution improves explainability. In: European Conference on Computer Vision.
2. Benz, P., Ham, S., Zhang, C., Karjauv, A., Kweon, I.S., 2021. Adversarial Robustness Comparison of Vision Transformer and MLP-Mixer to CNNs. In: British Machine Vision Conference.
3. Bhojanapalli, S., Chakrabarti, A., Glasner, D., Li, D., Unterthiner, T., Veit, A., 2021. Understanding robustness of transformers for image classification. In: Proceedings of the IEEE/CVF International Conference on Computer Vision.
4. On evaluating adversarial robustness;Carlini,2019
5. Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs;Chen;IEEE Trans. Pattern Anal. Mach. Intell.,2018
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献