huipinglin

Huiping Lin

Huiping Lin

linhuiping15@gmail.com
GitHub
Chongqing, China

Contact Address

Affiliation: School of Microelectronics and Communication Engineering, Chongqing University
Address: No. 174, Shazheng Street, Shapingba District, Chongqing, China
Portfolio: https://huipinglinn.github.io

Research Interests

SAR image understanding and interpretation, polarimetric SAR target detection and recognition, polarimetry, machine learning and computer vision.

Education

Tsinghua University — Beijing, China

Experience

Chongqing University — Professor

Chongqing, China | Dec 2024 – Present (Full-time)

Fudan University — Assistant Researcher

Shanghai, China | Jul 2022 – Nov 2024 (Full-time)

Publications

Journal Articles

  1. H. Lin, J. Yin, and J. Yang, “Learning quaternion convolutional neural networks for PolSAR target recognition,” IEEE Transactions on Aerospace and Electronic Systems, 2025

  2. H. Lin, X. Su, Z. Zeng, C. Xing, and J. Yin, “Speckle2self: Learning self-supervised despeckling with attention mechanism for SAR images,” Remote Sensing, vol. 17, no. 23, p. 3840, 2025

  3. Z. Zeng, Z. Chen, J. Yin, and H. Lin*, “Ship detection in SAR images using sparse R-CNN with wavelet deformable convolution and attention mechanism,” Remote Sensing, vol. 17, no. 23, p. 3794, 2025

  4. H. Lin, Z. Xie, L. Zeng, and J. Yin, “Multi-scale time-frequency representation fusion network for target recognition in SAR imagery,” Remote Sensing, vol. 17, no. 16, p. 2786, 2025.

  5. H. Lin, J. Yin, J. Yang, and F. Xu, “Interpreting neural network pattern with pruning for PolSAR target recognition,” IEEE Transactions on Geoscience and Remote Sensing, 2024.

  6. Y. Wang, H. Jia, S. Fu, H., H. Lin*, and F. Xu, “Reinforcement learning for SAR target orientation inference with the differentiable SAR renderer,” IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1–13, 2024.

  7. H. Lin, J. Yang, and F. Xu, “PolSAR target recognition with CNNs optimizing discrete polarimetric correlation pattern,” IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1–14, 2024.

  8. H. Lin, H. Wang, J. Yin, and J. Yang, “Local climate zone classification via semi-supervised multimodal multiscale transformer,” IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1–17, 2024.

  9. H. Lin, H. Wang, F. Xu, and Y.-Q. Jin, “Target recognition for SAR images enhanced by polarimetric information,” IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1–16, 2024.

  10. H. Lin, K. Jin, J. Yin, J. Yang, T. Zhang, F. Xu, and Y.-Q. Jin, “Residual in residual scaling networks for polarimetric SAR image despeckling,” IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1–17, 2023.

  11. H. Lin, H. Wang, J. Wang, J. Yin, and J. Yang, “A novel ship detection method via generalized polarization relative entropy for PolSAR images,” IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1–5, 2020.

  12. H. Lin, F. Yuan, C. Xing, and J. Yang, “An edge attention-based geodesic distance for PolSAR image superpixel segmentation,” Electronics Letters, vol. 56, no. 10, pp. 510–512, 2020.

  13. H. Lin, H. Chen, K. Jin, L. Zeng, and J. Yang, “Ship detection with superpixel-level Fisher vector in high-resolution SAR images,” IEEE Geoscience and Remote Sensing Letters, vol. 17, no. 2, pp. 247–251, 2019.

  14. H. Lin, H. Chen, H. Wang, J. Yin, and J. Yang, “Ship detection for PolSAR images via task-driven discriminative dictionary learning,” Remote Sensing, vol. 11, no. 7, p. 769, 2019.

  15. H. Lin, S. Song, and J. Yang, “Ship classification based on MSHOG feature and task-driven dictionary learning with structured incoherent constraints in SAR images,” Remote Sensing, vol. 10, no. 2, p. 190, 2018.

  16. Y. Xing, H. Lin, F. Wang, F. Xue, and F. Xu, “SAR2Canopy: A framework integrating scattering model with neural networks for canopy height estimation from airborne p-band SAR data,” IEEE Transactions on Geoscience and Remote Sensing, 2025.

  17. R. Li, J. Wei, H., H. Lin and F. Xu, “Learning terrain scattering models from massive multi-source earth observation data,” IEEE Transactions on Geoscience and Remote Sensing, 2025.

  18. L. Zeng, Y. Du, H. Lin, J. Wang, J. Yin, and J. Yang, “A novel region-based image registration method for multisource remote sensing images via CNN,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 1821–1831, 2020.

Conference Papers

  1. H. Lin, J. Yin, and J. Yang, “Revisiting the Contribution of Polarimetric Information to Target Recognition for SAR Images,” in IGARSS 2025 - 2025 IEEE International Geoscience and Remote Sensing Symposium, Brisbane, Australia, 2025, pp. 9122–9125.

  2. Z. Xie, H. Lin*, and F. Xu, “SAR Target Recognition Network Based on Time-Frequency Domain Channel Attention Mechanism,” in 2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP), Zhuhai, China, 2024, pp. 1–6.

  3. Z. Chen, H. Lin*, and F. Xu, “A Wavelet Feature Based SAR Ship Detection Algorithm in Sparse Framework,” in 2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP), Zhuhai, China, 2024, pp. 1–4.

  4. H. Lin, Y. Xing, Z. Chen, J. Yin, and J. Yang, “Edge Attention Superpixel Segmentation for Polarimetric SAR Images,” in IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 9770–9773.

  5. H. Lin and H. Wang, “A Novel Target Recognition Method with Polarimetric Correlation Phase for SAR Images,” in IET Conference Proceedings CP874, vol. 2023, no. 47, 2023, pp. 1152–1156.

  6. H. Lin, J. Yin, H. Wang, and J. Yang, “Edge Detection in PolSAR Images Based on Polarimetric Nonsubsampled Contourlet Transform,” in IET Conference Proceedings CP874, vol. 2023, no. 47, 2023, pp. 2817–2820.

  7. H. Lin, H. Wang, H. Chen, J. Yin, and J. Yang, “Ship Detection for Polarimetric SAR Images Via Graph-Based Sparse Manifold Ranking,” in IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 2193–2196.

  8. H. Lin, J. Bao, J. Yin, and J. Yang, “Superpixel Segmentation with Boundary Constraints for Polarimetric SAR Images,” in IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 2018, pp. 6195–6198.

  9. Y. Xing, H. Lin, J. Zhu, F. Wang, F. Xu, and W. Jiang, “Multisource Data Integration of Sentinel-1 and Sentinel-2 for Above Ground Biomass Inversion,” in 2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP), Zhuhai, China, 2024, pp. 1–4.

  10. Y. Xing, H. Lin, F. Xue, F. Wang, and F. Xu, “A Forest Parameter Inversion Method Based on Double-Bounce Scattering Components of Polarimetric P-Band SAR Data,” in IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 3599–3603.

  11. Y. Wang, H. Jia, S. Fu, H. Lin, and F. Xu, “Differentiable SAR Renderer Embedded Reinforcement Learning for View Angles Inversion in SAR Images,” in IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 1992–1995.

  12. R. Li, H. Lin, J. Wei, and F. Xu, “Utilizing Multisource Data: Inversion of Surface Texture Parameters and Generation of Multi-Angle SAR Images Through Physical Models,” in IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 3058–3061.

Awards & Achievements

Skills

Programming Languages: C/C++, Python, MATLAB
Technologies: Qt, MySQL, Git, Docker, OpenCV, PyTorch, TensorFlow

Download CV

Last updated: October 2025