孟哲
讲师 硕士生导师
西安邮电大学
个人简介
孟哲，男，1992年10月生，博士，中共党员，陕西铜川人。陕西高校青年创新团队核心成员，西安邮电大学“优秀导师团队”成员。
教育经历
2014年6月 获西安电子科技大学学士学位
2020年6月 获西安电子科技大学博士学位 本科直博 导师：焦李成教授
工作经历
2020年7月 至 今 西安邮电大学 通信与信息工程学院 讲师
研究方向
深度学习理论 高光谱遥感影像处理
孟哲，男，1992年10月生，博士，中共党员，陕西铜川人。陕西高校青年创新团队核心成员，西安邮电大学“优秀导师团队”成员。
2014年6月 获西安电子科技大学学士学位
2020年6月 获西安电子科技大学博士学位 本科直博 导师：焦李成教授
2020年7月 至 今 西安邮电大学 通信与信息工程学院 讲师
深度学习理论 高光谱遥感影像处理
| 22 | 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]//Proceedings of the 2025 IEEE International Geoscience and Remote Sensing Symposium, Accepted, 2025.(EI会议) | 2025 |
| 21 | Zhe Meng*, Qian Yan, Feng Zhao, Gaige Chen, Wenqiang Hua, and Miaomiao Liang, Global-local multigranularity transformer for hyperspectral image classification[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025, 18: 112-131. (二区)[Link] | 2025 |
| 20 | Jinglu He*, Ruiting Sun, Yingying Kong, Wenlong Chang, Chenglu Sun, Gaige Chen, Yinghua Li, Zhe Meng, and Fuping Wang, CPINet: Towards novel cross polarimetric interaction network for dual-polarized SAR ship classification[J]. Remote Sensing, 2024, 16(18): 3479. (二区)[Link] | 2024 |
| 19 | Zhe Meng*, Taizheng Zhang, Feng Zhao, Gaige Chen, and Miaomiao Liang, Multiscale super token transformer for hyperspectral image classification[J]. IEEE Geoscience and Remote Sensing Letters, 2024, 21: 5508105. (三区)[Link] | 2024 |
| 18 | Wenqiang Hua*, Qianjin Hou, Xiaomin Jin, Lin Liu, Nan Sun, and Zhe Meng, A feature fusion network for polsar image classification based on physical features and deep features[J]. IEEE Geoscience and Remote Sensing Letters, 2024, 21: 4012705. (三区)[Link] | 2024 |
| 17 | Miaomiao Liang, Xianhao Zhang, Xiangchun Yu*, Lingjuan Yu, Zhe Meng, Xiaohong Zhang, and Licheng Jiao, An efficient transformer with neighborhood contrastive tokenization for hyperspectral images classification[J]. International Journal of Applied Earth Observation and Geoinformation, 2024, 131: 103979. (一区)[Link] | 2024 |
| 16 | Feng Zhao, Junjie Zhang*, Zhe Meng, Hanqiang Liu, Zhenhui Chang, and Jiulun Fan, Multiple vision architectures-based hybrid network for hyperspectral image classification[J]. Expert Systems with Applications, 2023, 234: 121032. (一区)[Link] | 2023 |
| 15 | Zhe Meng*, Qian Yan, Feng Zhao, and Miaomiao Liang, Multi-scale feature attention and transformer for hyperspectral image classification[C]//Proceedings of the 2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, Athens, Greece, 2023: 1-5. (EI会议)[Link] | 2023 |
| 14 | Zhe Meng*, Qian Yan, Feng Zhao, and Miaomiao Liang, Hyperspectral image classification with dynamic spatial-spectral attention network[C]//Proceedings of the 2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, Athens, Greece, 2023: 1-4. (EI会议)[Link] | 2023 |
| 13 | Miaomiao Liang, Jian Dong, Lingjuan Yu*, Xiangchun Yu*, Zhe Meng, and Licheng Jiao, Self-supervised learning with learnable sparse contrastive sampling for hyperspectral image classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 5530713. (一区)[Link] | 2023 |
| 12 | Zhe Meng*, Licheng Jiao, Miaomiao Liang, and Feng Zhao, A lightweight spectral-spatial convolution module for hyperspectral image classification[J]. IEEE Geoscience and Remote Sensing Letters, 2022, 19: 5505105. (三区)[Link] | 2022 |
| 11 | Zhe Meng, Junjie Zhang, Feng Zhao*, Hanqiang Liu, and Zhenhui Chang, Residual dense asymmetric convolutional neural network for hyperspectral image classification[C]//Proceedings of the 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022: 3159-3162. (EI会议)[Link] | 2022 |
| 10 | Junjie Zhang, Zhe Meng*, Feng Zhao*, Hanqiang Liu, and Zhenhui Chang, Convolution transformer mixer for hyperspectral image classification[J]. IEEE Geoscience and Remote Sensing Letters, 2022, 19: 6014205. (三区)[Link] | 2022 |
| 9 | Miaomiao Liang, Huai Wang, Xiangchun Yu*, Zhe Meng, Jianbing Yi, and Licheng Jiao, Lightweight multilevel feature fusion network for hyperspectral image classification[J]. Remote Sensing, 2022, 14(1): 79. (二区)[Link] | 2022 |
| 8 | Miaomiao Liang, Qinghua He, Xiangchun Yu*, Huai Wang, Zhe Meng, and Licheng Jiao, A dual multi-head contextual attention network for hyperspectral image classification[J]. Remote Sensing, 2022, 14(13): 3091. (二区)[Link] | 2022 |
| 7 | Zhe Meng*, Feng Zhao, Miaomiao Liang, and Wen Xie, Deep residual involution network for hyperspectral image classification[J]. Remote Sensing, 2021, 13(16): 3055. (二区)[Link] | 2021 |
| 6 | Feng Zhao, Junjie Zhang, Zhe Meng*, and Hanqiang Liu, Densely connected pyramidal dilated convolutional network for hyperspectral image classification[J]. Remote Sensing, 2021, 13(17): 3396. (二区)[Link] | 2021 |
| 5 | Zhe Meng*, Feng Zhao, and Miaomiao Liang, SS-MLP: A novel spectral-spatial mlp architecture for hyperspectral image classification[J]. Remote Sensing, 2021, 13(20): 4060. (二区)[Link] | 2021 |
| 4 | 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. (二区)[Link] | 2021 |
| 3 | Zhe Meng, Lingling Li*, Licheng Jiao, Zhixi Feng, Xu Tang, and Miaomiao Liang, Fully dense multiscale fusion network for hyperspectral image classification[J]. Remote Sensing, 2019, 11(22): 2718. (二区)[Link] | 2019 |
| 2 | Miaomiao Liang*, Licheng Jiao, and Zhe Meng, A superpixel-based relational autoencoder for feature extraction of hyperspectral images[J]. Remote Sensing, 2019, 11(20): 2454. (二区)[Link] | 2019 |
| 1 | Zhe Meng, Lingling Li*, Xu Tang, Zhixi Feng, Licheng Jiao, and Miaomiao Liang, Multipath residual network for spectral-spatial hyperspectral image classification[J]. Remote Sensing, 2019, 11(16): 1896. (二区)[Link] | 2019 |
| 3 | 孟哲，张泰政，赵凤，陈改革，梁苗苗，基于超级词元Transformer的高光谱图像分类方法及装置，中国，申请号：202311761296.4。 | 2023 |
| 2 | 孟哲，张泰政，闫芊，赵凤，陈改革，梁苗苗，基于轻量级多尺度Transformer网络的高光谱图像分类方法及系统，中国，申请号：202311760700.6。 | 2023 |
| 1 | 孟哲，闫芊，岳攀，赵凤，益琛，陈改革，梁苗苗，基于动态卷积Transformer的高光谱图像分类方法及系统，中国，申请号：202311760963.7。 | 2023 |
| 陕西省教育厅科学研究计划，青年创新团队项目，24JP179，基于Mamba模型的高光谱遥感影像分类方法研究，2025.01-2026.12，在研，主持 | 2025 |
| 陕西省自然科学基础研究计划，青年项目，2022JQ-704，基于注意力动态混合连接网络的高光谱遥感影像分类研究，2022.01-2023.12，结题，主持 | 2022 |
| 陕西省教育厅科学研究计划，一般专项项目，22JK0556，基于视觉Transformer的高光谱遥感影像分类研究，2022.01-2023.12，结题，主持 | 2022 |
| 教育部产学合作协同育人项目，西邮-华为智能基座2.0，计算机视觉，2024.01-2025.12，在研，主持 | 2024 |
| 教育部产学合作协同育人项目，西邮-华为智能基座，计算机视觉，2022.01-2023.12，结题，主持 | 2022 |
| 数据挖掘与智能分析(双语，必修，48/32课时) | （2023, 2024, 2025） |
| 计算机视觉(选修，32课时) | （2023, 2024, 2025） |
| 分布式计算及应用(选修，32课时) | （2021, 2022, 2023, 2024, 2025） |
| 科研训练 | （2021, 2022） |
| 电子电路CAD技术(选修，32课时) | （2021, ） |
| IEEE Transactions on Geoscience and Remote Sensing |
| IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| International Journal of Digital Earth |
| Neurocomputing |
| Remote Sensing |
| Scientific Reports |
| Sensors |
| 通信地址： | 西安市长安区西长安街618号 |
| 电子邮箱： | zhemeng@xupt.edu.cn |
| 办公地点： | 通院大楼509 |