个人简介：陈黎辉，硕士生导师，通过“3+2+3”8年制本硕博连读于四川大学电子信息学院获得博士学位，期间于意大利国家研究院进行联合博士培养，导师Gemine Vivone, Jocelyn Chanussot (IEEE Fellow)。长期聚焦图像复原、遥感图像处理、多模态图像融合解译、遥感基础模型研究，主持国家自然科学基金青年项目、国家资助博士后人员计划（C档）、博士后面上项目、重庆市自然科学基金面上项目、中央高校基金和课题等多个项目，累计发表SCI论文40余篇，其中第一/通信作者在IEEE TNNLS、IEEE TGRS、IEEE TII、IEEE JSTARS、AAAI等期刊上发表学术论文20余篇（ESI高被引论文2篇），授权发明专利4项。主讲《现代机器学习》研究生课程、《人工智能基础》本科生课程，指导研究生获全国比赛一等奖1项、行业级铜奖1项，获中国学位与研究生教育学会优秀指导老师奖。长期担任AAAI、ACMMM、IEEE TIP、IEEE TNNLS、 IEEE TGRS、IEEE GRSL、IEEE TII、IEEE SPL、Information Fusion、 Pattern Recognition等期刊审稿专家。

每年招收硕士1-2名，欢迎有志于从事图像复原、遥感图像处理、计算机视觉、AI4GeoScience的同学报考课题组，可为研究兴趣相关、自驱力强的本科同学提供科研培训。攻读团队博士请联系团队负责人周喜川教授zxc@cqu.edu.cn。

主持项目：

6. 基于深度动态模型的开放场景光谱图像融合，国家自然科学基金青年项目，2024.1-2026.12，主持

5. 通用多源遥感图像融合大模型技术研究，国家资助博士后人员计划C档，2024.1-2025.12，主持，结题

4. 面向遥感图像融合超分辨率的强泛化深度模型研究，博后面上基金，2023.8-2025.7，主持，结题

3. 面向山火监测的热红外遥感数据预处理技术研究，重庆市自然科学基金面上项目，2024.7-2026.6，主持

2. xxxxxx，中央高校科研业务经费国防专项，2024.7-2025.6， 主持，结题

1. 高时效高精度数据传输、融合与决策机制研究，中央高校科研业务经费，2023.5-2024.5，参与，结题

部分论文：

• [20] L. Jian, J. Liu, S. Wu, L. Chen*, "CLIPPan: Adapting CLIP as A Supervisor for Unsupervised Pansharpening," AAAI Conference on Artificial Intelligence (AAAI), 2026.

• [19] X. Zhou, J. Zhao, L. Chen*, G. Vivone, Y. Liu, J. Nie, and H. Liu, "Multimodality Image Registration With Modality Distillation," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2025.

• [18] L. Chen, T. Song, L. Jian, D. Zhang, G. Vivone, and X. Zhou, "High-Fidelity Pansharpening via Trigeminal Pyramid Decoding of CNN-Transformer Encoded Features," IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2025.

• [17] L. Jian, J. Liu, L. Chen*, D. Zhang, G. Vivone, and X. Zhou, "Feature Interaction and Adaptive Fusion Network With Spectral Modulation for Pansharpening," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), vol. 18, pp. 10458-10470, 2025.

• [16] X. Su, X. Shen, M. Wan, J. Nie, L. Chen, H. Liu, & X. Zhou, "EigenSR: Eigenimage-bridged pre-trained RGB learners for single hyperspectral image super-resolution," AAAI Conference on Artificial Intelligence (AAAI), 39 (7), pp. 7033–7041, 2025.

• [15] R. Ding, L. Yong, S. Zhao, J. Nie, L. Chen, H. Liu, & X. Zhou, "Progressive fine-to-coarse reconstruction for accurate low-bit post-training quantization in vision transformers," Neural Networks, 107558, 2025.

• [14] H. Liu, J. Huang, J. Nie, J. Xie, L. Chen, & X. Zhou, "Density guided and frequency modulation dehazing network for remote sensing images," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2025.

• [13] X. Su, X. Shen, H. Liu, L. Chen, G. Vivone, & X. Zhou, "Toward model-independent separative training for deep hyperspectral anomaly detection with mask guidance," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2025.

• [12] X. Zhou, Q. Song, J. Nie, Y. Feng, H. Liu, F. Liang, L. Chen, & J. Xie, "Hybrid cross-modality fusion network for medical image segmentation with contrastive learning," Engineering Applications of Artificial Intelligence, 144, 110073, 2025.

• [11] M. Ashraf, L. Chen, N. Innab, M. Umer, J. Baili, T. Kim, and I. Ashraf, "Novel 3D Deep Neural Network Architecture for Crop Classification Using Remote Sensing-Based Hyperspectral Images," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2024.

• [10] A. Mahmood, L. Chen, X. Zhou, and M. AR., "A Joint Architecture of Mixed-Attention Transformer and Octave Module for Hyperspectral Image Denoising," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2024.

• [9] X. Zhou, F. Liang, L. Chen*, H. Liu, J. Nie, and J. Xie, "MeSAM: Multiscale Enhanced Segment Anything Model for Optical Remote Sensing Images," IEEE Transactions on Geoscience and Remote Sensing (TGRS), doi: 10.1109/TGRS.2024.3398038, 2024.

• [8] X. Shen, L. Chen, H. Liu, X. Su, W. Wei, X. Zhu, and X. Zhou, "Efficient Hyperspectral Sparse Regression Unmixing With Multilayers," IEEE Transactions on Geoscience and Remote Sensing (TGRS), vol. 61, pp. 1-14, 2023.

• [7] L. Chen, G. Vivone, J. Qin, J. Chanussot, and X. Yang, "Spectral-spatial Transformer for Hyperspectral Image Sharpening," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.

• [6] L. Chen, G. Vivone, Z. Nie, J. Chanussot, and X. Yang, "Spatial Data Augmentation: Improving the Generalization of Neural Networks for Pansharpening," IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2023.

• [5] L. Chen, Z. Lai, G. Vivone, G. Jeon, J. Chanussot, and X. Yang, "ArbRPN: A Bidirectional Recurrent Pansharpening Network for Multispectral Images with Arbitrary Numbers of Bands," IEEE Transactions on Geoscience and Remote Sensing (TGRS), vol. 60, pp. 1–18, 2022.

• [4] J. Qin, L. Chen, S. Jeon, and X. Yang, "Progressive Interaction-learning Network for Lightweight Single-Image Super-Resolution in Industrial Applications," IEEE Transactions on Industrial Informatics (TII), 2022.

• [3] L. Chen, G. Vivone, J. Qin, J. Chanussot, and X. Yang, "Spectral-spatial Transformer for Hyperspectral Image Sharpening," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2022.

• [2] L. Chen, R. Tang, M. Anisetti, and X. Yang, "A lightweight iterative error reconstruction network for infrared image super-resolution in smart grid," Sustainable Cities and Society, vol. 66, 2020.

• [1] L. Chen, X. Yang, G. Jeon, M. Anisetti, and K. Liu, "A trusted medical image super-resolution method based on feedback adaptive weighted dense network," Artificial Intelligence in Medicine, vol. 106, 2020.