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发布时间:2021/11/30

孟哲

Zhe Meng

 

讲师,硕士生导师

 

西安邮电大学 emc体育官网  信息工程系

 

高光谱遥感影像分类

 

zhemeng@xupt.edu.cn

个人简介

孟哲,讲师,男,199210月生,中共党员,工学博士。分别于2014年和2020年在西安电子科技大学获学士、博士学位,师从欧洲科学院外籍院士、俄罗斯自然科学院外籍院士焦李成教授。

主要研究方向为基于深度学习理论的高光谱遥感影像分类。相关研究成果已发表在 IEEE Transactions on Geoscience and Remote SensingIEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingIEEE Geoscience and Remote Sensing LettersExpert Systems With ApplicationsRemote Sensing等权威期刊和会议上。目前发表学术论文16篇,其中11篇作为第一作者或通讯作者。主持陕西省自然科学基金青年项目、陕西省教育厅一般专项科研计划项目各1项,参与多项国家自然科学基金项目。

欢迎对科研有兴趣的同学报考我的研究生,详情可访问我的个人主页https://zhe-meng.github.io/

教育背景

2014.09-2020.06 西安电子科技大学 博士

2010.08-2014.07 西安电子科技大学 本科

学术论文

[1] Zhe Meng*, Qian Yan, Feng Zhao, and Miaomiao Liang. Multi-scale feature attention and transformer for hyperspectral image classification[C]//Proceeding of the 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). Athens, Greece, 2023: 1-5.

[2] Zhe Meng*, Qian Yan, Feng Zhao, and Miaomiao Liang. Hyperspectral image classification with dynamic spatial-spectral attention network[C]//Proceeding of the 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). Athens, Greece, 2023: 1-4.

[3] 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 (GRSL), 2022, 19: 5505105.

[4] Zhe Meng, Junjie Zhang, Feng Zhao*, Hanqiang Liu, and Zhenhui Chang. Residual dense asymmetric convolutional neural network for hyperspectral image classification[C]//Proceeding of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Kuala Lumpur, Malaysia, 2022: 3159-3162.

[5] Zhe Meng*, Feng Zhao, Miaomiao Liang, and Wen Xie. Deep residual involution network for hyperspectral image classification[J]. Remote Sensing (RS), 2021, 13(16): 3055.

[6] 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 (JSTARS), 2021, 142494-2507.

[7] Zhe Meng*, Feng Zhao, and Miaomiao Liang. SS-MLP: A novel spectral-spatial MLP architecture for hyperspectral image classification [J]. Remote Sensing (RS), 2021, 13(20): 4060.

[8] 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 (RS), 2019, 11(16): 1896.

[9] 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.

[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 (GRSL), 2022, 19: 6014205.

[11] 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.

[12] 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 (ESWA), 2023, 234: 121032.

[13] 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.

[14] Miaomiao Liang, Huai Wang, Xiangchun Yu*, Zhe Meng, Jianbing Yi, and Licheng Jiao. Lightweight multilevel feature fusion network for hyperspectral images classification[J]. Remote Sensing, 2022, 14(1): 79.

[15] 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 (TGRS), 2023.

[16] Miaomiao Liang, Qinghua He, Xiangchun Yu*, Huai Wang, Zhe Meng, and Licheng Jiao. A dual multi-head contextual self-attention network for hyperspectral image classification[J]. Remote Sensing, 2022, 14(13):3091.

科研项目

[1] 陕西省自然科学基础研究计划,一般项目-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,在研,主持  

[2] 陕西省教育厅一般专项科研计划项目,自然科学专项, 22JK0556,基于视觉Transformer的高光谱遥感影像分类研究,2022/01-2023/12,在研,主持  

[3] 陕西省自然科学基础研究计划,一般项目(青年)2023-JC-QN-0767,基于条件归一化生成式网络的近红外图像上色方法研究,2023/01-2024/12,在研,参与

[4] 国家自然科学基金委员会,面上项目, 62271390,空间电源知识驱动多源无标签数据融合的服役状态增强感知评估方法,2023/01-2026/12,在研,参与  

[5] 国家自然科学基金委员会,面上项目, 61877066,数据驱动的混合逆问题cGANs回归及其在高光谱数据解混中的应用,2019/01-2022/12,结题,参与

招生信息

欢迎积极主动,踏实勤奋,对科研感兴趣的同学报考我的研究生。联系的最佳方式是邮件,可在该页面查看我指导的研究生的学业情况。

联系方式

联系邮箱:zhemeng@xupt.edu.cn

个人主页:https://zhe-meng.github.io

办公地点:通院大楼509

联系地址:陕西省西安市长安区西长安街618号西安邮电大学,邮编:710121

 

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