Haimiao Zhang

Recent Publications

1. Jiqing Wu, Haimiao Zhang\(^\dagger\), Chang Liu, Jun Qiu, KPF-Net: KAN perception and fusion network for infrared small target detection. Infrared Physics & Technology, Volume 153, January 2026, 106294. [DOI, Journal]

2. Haiyan Guo, Haimiao Zhang, Jun Qiu. Preconditioned stochastic gradient Langevin dynamics for light field denoising. Signal Processing. Volume 238, pp: 110097, 2026. [DOI, Journal]

3. 朱桐, 张海苗, 邱钧. 基于提示学习的鸟类细粒度识别增量学习方法. 激光与光电子学进展,61(24): 2437008, 2024.

4. Haocheng Ju, Haimiao Zhang\(^\dagger\), Lin Li, Xiao Li, Bin Dong. A Comparative Study of Deep Learning and Iterative Algorithms for Joint Channel Estimation and Signal Detection in OFDM Systems. Signal Processing. Volume 223, pp: 109554, 2024. DOI:10.1016/j.sigpro.2024.109554 [Journal, arXiv]

5. Huazhen Chen, Haimiao Zhang, Chang Liu, Jianpeng An, Zhongke Gao, Jun Qiu. FET-FGVC: Feature-enhanced Transformer for Fine-grained Visual Classification. Pattern Recognition. 2024. DOI:10.1016/j.patcog.2024.110265.

6. Haiyan Guo, Jun Qiu, Haimiao Zhang\(^\dagger\). Light Field Denoising with Adaptive Stochastic Gradient Langevin Dynamics. in Frontiers in Optics + Laser Science 2023 (FiO, LS), Technical Digest Series (Optica Publishing Group, 2023), paper JM7A.78.

7. 梁丹, 张海苗, 邱钧. 基于自监督学习的光场空间域超分辨成像. 激光与光电子学进展. 61(04), 2024. DOI:10.3788/LOP231188.

8. Haimiao Zhang, Bin Dong, Ge Wang, Baodong Liu. Deep Learning for CT Image Reconstruction. In J. Ye, Y. Eldar, & M. Unser (Eds.), Deep Learning for Biomedical Image Reconstruction (pp. 89-113). Cambridge: Cambridge University Press. 2023. DOI:10.1017/9781009042529.008. Online ISBN:9781009042529

9. Ce Wang, Kun Shang, Haimiao Zhang, Shang Zhao, Dong Liang, S. Kevin Zhou. Active CT Reconstruction with a Learned Sampling Policy, Proceedings of the 31st ACM International Conference on Multimedia, October, Pages 7226–7235, 2023. [Proceedings, arXiv]

10. Shurun Gao, Chang Liu, Haimiao Zhang, Zhehai Zhou, and Jun Qiu. “Multiscale Attention‑based Detection of Tiny Targets in Aerial Beach Images”. In: Front. Mar. Sci. 9 (2022). DOI: 10.3389/fmars.2022.1073615.

11. Zhicheng Hao, Jun Qiu, Haimiao Zhang, Guangbo Ren, and Chang Liu. “UMOTMA: Underwater multiple object tracking with memory aggregation”. In: Front. Mar. Sci. 9 (2022). DOI: 10.3389/fmars.2022.1071618.

12. Dan Liang, Haimiao Zhang\(^\dagger\), Jun Qiu. Self-Supervised Learning for Spatial Domain Light Field Super-Resolution. Frontiers in Optics + Laser Science (FiOLS). JW5B.63, 2022.

13. Zhicheng Hao, Chang Liu, Haimiao Zhang, Jun Qiu. Multiple Object Tracking Based on Deep LSTM. Frontiers in Optics + Laser Science (FiOLS). JW4B.63, 2022.

14. Shurun Gao, Chang Liu, Haimiao Zhang, Jun Qiu. Tiny Target Detection Based on Multi-scale Attention. Frontiers in Optics + Laser Science (FiOLS). JW4B.64, 2022.

15. Wang, Hong, Yuexiang Li, Haimiao Zhang, Deyu Meng, Yefeng Zheng. InDuDoNet+: A Model-Driven Interpretable Dual Domain Network for Metal Artifact Reduction in CT Images. In: Medical Image Analysis. Volume 85: 102729, April 2023. DOI: 10.1016/j.media.2022.102729. [arXiv]

16. Wang, Ce, Kun Shang, Haimiao Zhang, Qian Li, and S. Kevin Zhou. “DuDoTrans: Dual‑Domain Transformer for Sparse‑View CT Reconstruction”. In: Machine Learning for Medical Image Reconstruction. Ed. by Nandinee Haq, Patricia Johnson, Andreas Maier, Chen Qin, Tobias Wurfl, and Jaejun Yoo. Cham: Springer International Publishing, 2022, pp. 84–94. [arXiv]

17. Wang, Hong, Yuexiang Li, Haimiao Zhang, Jiawei Chen, Kai Ma, Deyu Meng, Yefeng Zheng. "InDuDoNet: An Interpretable Dual Domain Network for CT Metal Artifact Reduction." MICCAI, pp: 107-118, 2021. (arXiv: 2109.05298) [arXiv, Journal]

18. Wang, Ce, Haimiao Zhang, Qian Li, Kun Shang, Yuanyuan Lyu, Bin Dong, and S. Kevin Zhou. "Improving Generalizability in Limited-Angle CT Reconstruction with Sinogram Extrapolation." MICCAI, pp: 86-96, 2021. (arXiv:2103.05255) [arXiv, Journal]

19. Zhang, Haimiao, Baodong Liu, Hengyong Yu, and Bin Dong. "MetaInv-Net: Meta Inversion Network for Sparse View CT Image Reconstruction." IEEE Transactions on Medical Imaging. 40(2): 621-634, 2021. DOI: 10.1109/TMI.2020.3033541. [arXiv, Journal, Code]

20. Zhang, Haimiao, and Bin Dong. "A Review on Deep Learning in Medical Image Reconstruction." Journal of the Operations Research Society of China. 8: 311–340, 2020. [arXiv, ResearchGate, Journal]

21. Zhang, Haimiao, Bin Dong, and Baodong Liu. "JSR-Net: A Deep Network for Joint Spatial-radon Domain CT Reconstruction from Incomplete Data." In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3657-3661. IEEE, 2019.[arXiv, ResearchGate, Journal]

22. Zhang, Haimiao, Bin Dong, and Baodong Liu. "A Reweighted Joint Spatial-Radon Domain CT Image Reconstruction Model for Metal Artifact Reduction." SIAM Journal on Imaging Sciences. 11(1): 707-733, 2018. [arXiv, Journal]

23. Zhang, Haimiao, Yichuan Dong, and Qibin Fan. "Wavelet Frame based Poisson Noise Removal and Image Deblurring." Signal Processing. 137: 363-372, 2017. [ResearchGate, Journal]

Preprints

1. Haocheng Ju, Haimiao Zhang\(^\dagger\), Lin Li, Xiao Li, Bin Dong. A Comparative Study of Deep Learning and Iterative Algorithms for Joint Channel Estimation and Signal Detection, arXiv:2303.03678. [arXiv ]

\(^\dagger\): Corresponding author.

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