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Springer International Publishing
Reference36 articles.
1. Akhtar, N., Liu, J., Mian, A.: Defense against universal adversarial perturbations. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 3389–3398 (2018)
2. Alzantot, M., Sharma, Y., Chakraborty, S., Zhang, H., Hsieh, C.J., Srivastava, M.B.: Genattack. In: Proceedings of the Genetic and Evolutionary Computation Conference (Jul 2019)
3. Baioletti, M., Coello, C.A.C., Di Bari, G., Poggioni, V.: Multi-objective evolutionary GAN. In: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, pp. 1824–1831. GECCO 2020, Association for Computing Machinery, New York, NY, USA (2020)
4. Bhattad, A., Chong, M.J., Liang, K., Li, B., Forsyth, D.: Unrestricted adversarial examples via semantic manipulation. In: ICLR (2020)
5. Carlini, N., Wagner, D.: Towards evaluating the robustness of neural networks. In: 2017 IEEE Symposium on Security and Privacy (SP), pp. 39–57 (2017)
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