The DOI matches its Crossref record; 156 of the 156 references it cites were found in a registry or an index.
A comprehensive survey on robust image watermarking
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Cites
Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2003.819861 · Cited by 57,892
Microsoft COCO: Common Objects in Context
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_48 · Cited by 45,460
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
(1993) · doi:10.1109/cvpr.1993 · Cited by 17,667
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Zhang, K., Zuo, W., Chen, Y., Meng, D., & Zhang, L. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2662206 · Cited by 8,983
Intriguing properties of neural networks
Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., & Fergus, R. (2013) · arXiv · doi:10.48550/arxiv.1312.6199 · Cited by 8,143
A review on the attention mechanism of deep learning
Niu, Z., Zhong, G., & Yu, H. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.03.091 · Cited by 3,379
Self-citationA Neural Algorithm of Artistic Style
Gatys, L., Ecker, A., & Bethge, M. (2016) · Journal of Vision · doi:10.1167/16.12.326 · Cited by 2,612
Petitcolas, F. A. P., Anderson, R. J., & Kuhn, M. G. (1999) · Proceedings of the IEEE · doi:10.1109/5.771065 · Cited by 2,546
Natural Image Statistics and Neural Representation
Simoncelli, E. P., & Olshausen, B. A. (2001) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.24.1.1193 · Cited by 2,460
Recovering high dynamic range radiance maps from photographs
Debevec, P. E., & Malik, J. (2008) · ACM SIGGRAPH 2008 classes · doi:10.1145/1401132.1401174 · Cited by 2,399
Cited by
Meng, F.-Q., & Wu, G. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.124413 · Cited by 144
Hou, Z., Yan, H., Zhang, L., Ren, N., Ma, R., & Qu, R. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3575574 · Cited by 3
Protecting Language Models Against Unauthorized Distillation through Trace Rewriting
Ma, X., Yeoh, W., Zhang, N., & Vorobeychik, Y. (2026) · arXiv · doi:10.48550/arxiv.2602.15143
“On the other hand, model watermarking (Liang et al., 2024b; Wan et al., 2022) operates on model outputs.”
Metadata
- Authors
- Wan, W., Wang, J., Zhang, Y., Li, J., Yu, H., & Sun, J.
- Venue
- Neurocomputing
- Publisher
- Elsevier BV
- Published
- 2022-06
- Volume
- 488
- Pages
- 226-247
- ISSN
- 0925-2312 (ISSN-L)
- OpenAlex
- W4214851787
- Cited by
- 264
- References
- 156
- FWCI
- 17.81
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wan, W., Wang, J., Zhang, Y., Li, J., Yu, H., & Sun, J. (2022). A comprehensive survey on robust image watermarking. Neurocomputing. https://doi.org/10.1016/j.neucom.2022.02.083
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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