The DOI matches its Crossref record; 262 of the 262 references it cites were found in a registry or an index.
Super-resolution: a comprehensive survey
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Citations
Cites
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
(1993) · doi:10.1109/cvpr.1993 · Cited by 17,667
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
(1993) · Proceedings of IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1993.341010 · Cited by 14,265
Advances in Neural Information Processing Systems 14: Proceedings of the 2001 Conference
(2002) · The MIT Press eBooks · doi:10.7551/mitpress/1120.001.0001 · Cited by 8,890
Image Super-Resolution Via Sparse Representation
Yang, J., Wright, J., Huang, T. S., & Ma, Y. (2010) · IEEE Transactions on Image Processing · doi:10.1109/tip.2010.2050625 · Cited by 5,217
Super-resolution image reconstruction: a technical overview
Park, S. C., Park, M. K., & Kang, M. G. (2003) · IEEE Signal Processing Magazine · doi:10.1109/msp.2003.1203207 · Cited by 3,282
Example-based super-resolution
Freeman, W. T., Jones, T. R., & Pasztor, E. C. (2002) · IEEE Computer Graphics and Applications · doi:10.1109/38.988747 · Cited by 2,498
Review article Multisensor image fusion in remote sensing: Concepts, methods and applications
Pohl, C., & Van Genderen, J. L. (1998) · International Journal of Remote Sensing · doi:10.1080/014311698215748 · Cited by 2,211
Fast and Robust Multiframe Super Resolution
Farsiu, S., Robinson, M. D., Elad, M., & Milanfar, P. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2004.834669 · Cited by 2,090
Improving resolution by image registration
Irani, M., & Peleg, S. (1991) · CVGIP: Graphical Models and Image Processing · doi:10.1016/1049-9652(91)90045-l · Cited by 1,929
Super-resolution through neighbor embedding
Chang, H., Yeung, D.-Y., & Xiong, Y. (2004) · Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004. · doi:10.1109/cvpr.2004.1315043 · Cited by 1,902
Cited by
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Ledig, C., Theis, L., Huszar, F., Caballero, J., Cunningham, A., Acosta, A., Aitken, A., Tejani, A., Totz, J., Wang, Z., et al. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.19 · Cited by 12,696
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Ledig, C., Theis, L., Huszár, F., Caballero, J., Cunningham, A., Acosta, A., Aitken, A. P., Tejani, A., Totz, J., Wang, Z., et al. (2016) · arXiv (Cornell University) · doi:10.17863/cam.51996 · Cited by 987
Image super-resolution: the techniques, applications, and future
Yue, L., Shen, H., Li, J., Yuan, Q., Zhang, H., & Zhang, L. (2016) · Signal Processing · doi:10.1016/j.sigpro.2016.05.002 · Cited by 554
A Review of the Deep Learning Methods for Medical Images Super Resolution Problems
Li, Y., Sixou, B., & Peyrin, F. (2021) · IRBM · doi:10.1016/j.irbm.2020.08.004 · Cited by 281
Illuminating the dark spaces of healthcare with ambient intelligence
Haque, A., Milstein, A., & Fei-Fei, L. (2020) · Nature · doi:10.1038/s41586-020-2669-y · Cited by 274
Metadata
- Authors
- Nasrollahi, K., & Moeslund, T. B.
- Venue
- Machine Vision and Applications
- Published
- 2014-06-14
- Volume
- 25
- Issue
- 6
- Pages
- 1423-1468
- ISSN
- 0932-8092 (ISSN-L)
- 1432-1769
- OpenAlex
- W1973788353
- Cited by
- 684
- References
- 262
- FWCI
- 43.03
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Super-resolution: a comprehensive survey. https://app.cochat.ai/papers/10.1007/s00138-014-0623-4
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- Nasrollahi, K., & Moeslund, T. B. (2014). Super-resolution: a comprehensive survey. Machine Vision and Applications. https://doi.org/10.1007/s00138-014-0623-4
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
