The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
GAN review: Models and medical image fusion applications
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Citations
Cites
Learning representations by back-propagating errors
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986) · Nature · doi:10.1038/323533a0 · Cited by 31,892
Unpaired image-to-image translation using cycle-consistent adversarial networks
Zhu, J.-Y., Park, T., Isola, P., & Efros, A. A. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.244 · Cited by 23,602
Auto-Encoding Variational Bayes
Kingma, D. P., & Welling, M. (2013) · arXiv · doi:10.48550/arxiv.1312.6114 · Cited by 20,067
Conditional Generative Adversarial Nets
Mirza, M., & Osindero, S. (2014) · arXiv · doi:10.48550/arxiv.1411.1784 · Cited by 8,863
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
Kim, J., Lee, J. K., & Lee, K. M. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.182 · Cited by 7,870
The Laplacian pyramid as a compact image code
Burt, P., & Adelson, E. (1983) · IEEE Transactions on Communications · doi:10.1109/tcom.1983.1095851 · Cited by 6,077
Proceedings of the 25th international conference on Machine learning
Cohen, W. W., McCallum, A., & Roweis, S. T. (2008) · Cited by 5,691
2009 IEEE Conference on Computer Vision and Pattern Recognition
(2009) · doi:10.1109/cvpr14067.2009 · Cited by 5,550
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
(2018) · doi:10.1109/cvpr40276.2018 · Cited by 4,737
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
Wang, X., Yu, K., Wu, S., Gu, J., Liu, Y., Dong, C., Qiao, Y., & Loy, C. C. (2019) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-11021-5_5 · Cited by 4,731
Cited by
XAI-based Clinical Decision Support System: A Systematic Review
Kim, S., Kim, D., Kim, M., Ko, H., & Jeong, O. (2024) · doi:10.20944/preprints202406.0721.v1 · Cited by 72
Dai, R., Jian, A., Zhang, R., Jia, Y., Mo, L., Zhan, S., & He, T. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.116272
Metadata
- Authors
- Zhou, T., Li, Q., Lu, H., Cheng, Q., & Zhang, X.
- Venue
- Information Fusion
- Publisher
- Elsevier BV
- Published
- 2023-03
- Volume
- 91
- Pages
- 134-148
- ISSN
- 1566-2535 (ISSN-L)
- OpenAlex
- W4306954497
- Cited by
- 268
- References
- 57
- FWCI
- 17.64
- Type
- journal article
- Language
- en
- Open access
- closed
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: GAN review: Models and medical image fusion applications. https://app.cochat.ai/papers/10.1016/j.inffus.2022.10.017
- The paper
- Zhou, T., Li, Q., Lu, H., Cheng, Q., & Zhang, X. (2023). GAN review: Models and medical image fusion applications. Information Fusion. https://doi.org/10.1016/j.inffus.2022.10.017
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.
