Correction to: Nature Communications https://doi.org/10.1038/s41467-023-40499-0, published online 15 August 2023
The original version of this Article included incorrect acknowledgements to the sources of Fig. 1c. The following sentence in the original caption to Fig. 1 “Illustration images in this Figure were obtained with permission from33,35.” has been changed to “Illustration images in panel (c) were obtained with permission from Papernot et al.70, Nguyen et al.71, and Athalye et al.72, left to right, respectively.”
The following missing references have also been added to the reference list:
[70] Papernot, N. et al. The limitations of deep learning in adversarial settings. In 2016 IEEE European symposium on security and privacy (EuroS&P), 372–387 (IEEE, 2016).
[71] Nguyen, A., Yosinski, J. & Clune, J. Deep neural networks are easily fooled: High confidence predictions for unrecognizable images. In Proceedings of the IEEE conference on computer vision and pattern recognition, 427–436 (2015).
[72] Athalye, A., Engstrom, L., Ilyas, A. & Kwok, K. Synthesizing robust adversarial examples. In International conference on machine learning, 284–293 (PMLR, 2018).
This has been corrected in the PDF and HTML versions of the Article.
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Veerabadran, V., Goldman, J., Shankar, S. et al. Author Correction: Subtle adversarial image manipulations influence both human and machine perception. Nat Commun 15, 543 (2024). https://doi.org/10.1038/s41467-024-44826-x
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DOI: https://doi.org/10.1038/s41467-024-44826-x