学位/职称：工学博士/副教授/博士生导师/硕士生导师

学科专业：计算机科学与技术

电子邮箱或联系电话：liangmiaom@jxust.edu.cn

讲授课程： 本科生课程：计算机视觉、离散数学    

研究生课程： 泛函分析

代表性论文：

[1] Miaomiao Liang, Weigang Wu, Huifang Shen*, Lingjuan Yu, Xiangchun Yu, and Licheng Jiao. SuperCoT-X: Masked hyperspectral image modeling with diverse superpixel-level contrastive tokenizer[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2025, 18: 17988. (IF:5.3, SCI二区) Code: https://github.com/sakurashine/HiBiCo

[2] Jian Dong, Miaomiao Liang, Zhi He*, and Chengle Zhou. Hierarchical and bidirectional contrastive learning for hyperspectral image classification[J]. IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2025, 63: 5517717. (IF:8.6, SCI一区) Code: https://github.com/JXUSTHyperSpectralImage/SuperCoT

[3] Zihan Chen, Miaomiao Liang*, Weiwei Wu, Siyu Yang, Zhe Meng and Lingjuan Yu, An adaptive sparse transformer with convolution mixer for hyperspectral image classification[C]//Proceeding of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Brisbane, Australia, 2025, pp. 2319-2323. 墙报展示

[4] Miaomiao Liang, Xianhao Zhang, Xiangchun Yu, Lingjuan Yu, Zhe Meng, Xiaohong Zhang, Licheng Jiao. An efficient Transformer with neighborhood contrastive tokenization for hyperspectral images classification[J]. International Journal of Applied Earth Observation and Geoinformation (JAG), 2024, 131:103979.（IF:8.6, SCI一区, Top）, Code: https://github.com/zoegnov07/NeiCoT

[5] Miaomiao Liang, Zuo Liu, Jian Dong, Lingjuan Yu, Xiangchun Yu, Jun Li, Licheng Jiao. ConVaT: A variational generative transformer with momentum contrastive learning for hyperspectral image classification[J]. IEEE Geoscience and Remote Sensing Letters (GRSL), 2024, 21: 1-5.（IF: 4.4, SCI三区）Code: https://github.com/liuzuo-byte/ConVaT

[6] Miaomiao Liang, Jian Dong, Lingjuan Yu, Xiangchun Yu, Zhe Meng, Licheng Jiao. Self-supervised learning with learnable sparse contrastive sampling for hyperspectral image classification[J]. IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2023, 61: 5530713.（IF: 8.6, SCI一区）Code: https://github.com/sakurashine/LSCoSa

[7] Miaomiao Liang, Qinghua He, Xiangchun Yu, Huai Wang, Zhe Meng, Licheng Jiao. A dual multi-head contextual attention network for hyperspectral image classification[J]. Remote Sensing, 2022, 14(13): 1-21. Code: https://github.com/mrpokere/DMuCA

[8] Huai Wang, Qinghua He, and Miaomiao Liang^#. A Multi-level Mixed Perception Network for Hyperspectral Image Classification[C], International Conference on Intelligence Science, 2022, Intelligence Science IV: 284-293.（分会报告）Code: https://github.com/JXUST-HyperSpectralImage/MMPN

[9] Miaomiao Liang, Huai Wang, Xiangchun Yu, Zhe Meng, Jianbing Yi, Licheng Jiao. Lightweight multilevel feature fusion network for hyperspectral image classification[J], Remote Sensing, 2022, 14(1): 79:1-20.（IF: 4.1, SCI二区）Code: https://github.com/JXUST-HyperSpectralImage/LMFN

[10] Miaomiao Liang, Licheng Jiao, and Chundong Xu. Deep feature-based multitask joint sparse representation for hyperspectral image classification[J]. IEEE Geoscience and Remote Sensing Letters (GRSL), 2020, 17(9):1578-1582.（IF: 4.4, SCI二区）

[11] Miaomiao Liang, Licheng Jiao, and Zhe Meng. A superpixel-based relational auto-encoder for feature extraction of hyperspectral images[J]. Remote Sensing, 2019, 11(20): 2454.（IF: 4.1, SCI二区, Top）

[12] Miaomiao Liang, Licheng Jiao, Shuyuan Yang, Fang Liu, Biao Hou, Huan Chen. Deep multiscale spectral-spatial feature fusion for hyperspectral images classification[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2018, 11(8): 2911-2924.（IF:5.3, SCI二区）

[13] Licheng Jiao, Miaomiao Liang^#, Huan Chen, Shuyuan Yang, Hongying Liu, and Xianghai Cao. Deep fully convolutional network-based spatial distribution prediction for hyperspectral image classification[J]. IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2017, 55(10): 5585-5599. (IF:8.6, SCI一区)

主持课题：

1、国家自然科学基金青年基金项目, 61901198, 基于多模态深层交互编码的小样本高光谱遥感影像分类方法研究, 2020/01-2022/12, 结题, 主持

2、国家自然科学基金地区基金项目, 62266020, 多视角注意力机制下的高光谱图像分类方法研究, 2023/01-2026/12, 在研, 主持

3、国家自然科学基金地区基金项目, 62566028, 面向高光谱图像分类域泛化建模的细粒度提示学习方法研究, 2026/01-2029/12, 在研, 主持

4、江西省自然科学基金青年基金项目, 20224BAB212008, 面向高光谱遥感影像解译的空谱自监督学习方法研究, 2023/01-2025/12, 结题, 主持

5、江西理工大学清江青年优秀人才支持计划资助, JXUSTQJYX2020019, 小样本高光谱遥感数据的地物精准识别与定位, 2021/01-2025/12, 在研, 主持

6、江西理工大学博士科研启动基金项目, jxxjbs19006, 基于多尺度几何稀疏编码的遥感图像特征学习, 2019/01-2021/12, 结题, 主持

参与在研课题：

1、国家自然科学基金地区基金项目, 62066018, 面向视频监控的时空注意力深度强化学习多目标跟踪研究, 2021/01-2024/12, 在研, 参与

2、国家自然科学基金地区基金项目, 62062037, 赣南山区地形无线传感器网络动态覆盖优化算法与路由协议研究, 2021/01-2024/12, 在研, 参与

3、国家自然科学基金地区基金项目, 62261027, 多维特征下基于极化CSAR二维图像的人造目标三维自动重建研究, 2023/01-2026/12, 在研, 参与