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Peng, Heqi; Chen, Mingxuan; Wang, Yunhong; Guo, Yuanfang (2026) HFA2RE: Enhancing adversarial robustness via Hyperspherical Feature Aggregation. Pattern Recognition, 169. doi:10.1016/j.patcog.2025.111857

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Reference TypeJournal (article/letter/editorial)
TitleHFA2RE: Enhancing adversarial robustness via Hyperspherical Feature Aggregation
JournalPattern Recognition
AuthorsPeng, HeqiAuthor
Chen, MingxuanAuthor
Wang, YunhongAuthor
Guo, YuanfangAuthor
Year2026 (January)Volume169
PublisherElsevier BV
DOIdoi:10.1016/j.patcog.2025.111857Search in ResearchGate
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Mindat Ref. ID18581672Long-form Identifiermindat:1:5:18581672:8
GUID0
Full ReferencePeng, Heqi; Chen, Mingxuan; Wang, Yunhong; Guo, Yuanfang (2026) HFA2RE: Enhancing adversarial robustness via Hyperspherical Feature Aggregation. Pattern Recognition, 169. doi:10.1016/j.patcog.2025.111857
Plain TextPeng, Heqi; Chen, Mingxuan; Wang, Yunhong; Guo, Yuanfang (2026) HFA2RE: Enhancing adversarial robustness via Hyperspherical Feature Aggregation. Pattern Recognition, 169. doi:10.1016/j.patcog.2025.111857
In(2026) Pattern Recognition Vol. 169. Elsevier BV

References Listed

These are the references the publisher has listed as being connected to the article. Please check the article itself for the full list of references which may differ. Not all references are currently linkable within the Digital Library.

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Not Yet Imported: - book-chapter : 10.1007/978-3-031-20056-4_42

If you would like this item imported into the Digital Library, please contact us quoting Book ID 9783031200557
T. Chen, S. Kornblith, M. Norouzi, G. Hinton, A simple framework for contrastive learning of visual representations, in: International Conference on Machine Learning, 2020, pp. 1597–1607.
Not Yet Imported: - proceedings-article : 10.1109/CVPR42600.2020.00975

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Not Yet Imported: - journal-article : 10.1609/aaai.v37i12.26733

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T. Wang, P. Isola, Understanding contrastive representation learning through alignment and uniformity on the hypersphere, in: International Conference on Machine Learning, 2020, pp. 9929–9939.
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Not Yet Imported: - journal-article : 10.1109/TIFS.2024.3359820

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E. Wong, L. Rice, J.Z. Kolter, Fast is better than free: Revisiting adversarial training, in: International Conference on Learning Representations, 2020.
L. Li, M.W. Spratling, Data augmentation alone can improve adversarial training, in: International Conference on Learning Representations, 2023.
Rebuffi (2021) Adv. Neural Inf. Process. Syst. Data augmentation can improve robustness 34, 29935
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Not Yet Imported: Machine Learning - journal-article : 10.1023/A:1007612920971

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Not Yet Imported: - proceedings-article : 10.1145/325334.325242

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Krizhevsky (2009) Citeseer Learning multiple layers of features from tiny images
A. Coates, A.Y. Ng, H. Lee, An Analysis of Single-Layer Networks in Unsupervised Feature Learning, in: International Conference on Artificial Intelligence and Statistics, Vol. 15, 2011, pp. 215–223.
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