导师信息
姓名：梁苗苗
学位/职称：工学博士/副教授
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
研究方向：计算机视觉、机器学习、遥感影像处理
情况简介：人工智能党支部书记、教研室副主任，入选江西理工大学“清江青年优秀人才支持计划”。主持国家自然科学基金项目2项，参与3项，主持江西省自然科学基金项目1项，省部级教改课题1项，以第一作者、通信作者或合作发表论文20余篇。担任IEEE TNNLS、IEEE TGRS、IEEE TCI、Neurocomputing等学术期刊审稿人。
DBLP: https://dblp.org/pid/206/6903.html
代表性论文：
[1] 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.（SCI一区, Top）, Code: https://github.com/zoegnov07/NeiCoT
[2] 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.（SCI三区）Code: https://github.com/liuzuo-byte/ConVaT
[3] Miaomiao Liang, Jian Dong, Lingjuan Yu, Xiangchun Yu, Zhe Meng, Licheng Jiao. Self-supervised learning with learnable sparse contrastive sampling for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2023, 61: 5530713.（SCI一区）Code: https://github.com/sakurashine/LSCoSa
[4] 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.（SCI二区, Top）Code: https://github.com/mrpokere/DMuCA
[5] 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
[6] 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.（SCI二区, Top）Code: https://github.com/JXUST-HyperSpectralImage/LMFN
[7] 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.（SCI二区）
[8] 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.（SCI二区, Top）
[9] 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.（SCI二区）
[10] 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. (SCI一区, Top)
[11] Xiangchun Yu, Hechang Chen, Miaomiao Liang#, Qing Xu, Lifang He. A transfer learning-based novel fusion convolutional neural network for breast cancer histology classification[J]. Multimedia Tools and Applications. 2020, 1-15.（SCI三区）
[12] Xiangchun Yu, Wei Pang, Qing Xu#, Miaomiao Liang#. Mammographic image classification with deep fusion learning[J]. Scientific Reports. 2020, 14361.1-11.（SCI三区）
[13] Zhe Meng, Licheng Jiao, Miaomiao Liang and Feng Zhao. Hyperspectral image classification with mixed link networks[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 2494-2507.（SCI三区）
[14] Zhe Meng, Feng Zhao, Miaomiao Liang. SS-MLP: A novel spectral-spatial MLP architecture for hyperspectral image classification[J]. Remote Sensing, 2021, 13(20): 4060.（SCI二区, Top）
[15] Zhe Meng, Licheng Jiao, Miaomiao Liang, Feng Zhao. A lightweight spectral-spatial convolution module for hyperspectral image classification[J]. IEEE Geoscience and Remote Sensing Letters, 2021, 19: 1-5.（SCI二区）
[16] Huan Chen, Licheng Jiao, Miaomiao Liang, Fang Liu, Shuyuan Yang, Biao Hou. Fast unsupervised deep fusion network for change detection of multitemporal SAR images [J]. Neurocomputing, 2019, 332: 56-70.（SCI二区）
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、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, 在研, 主持
4、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
5、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
