Zhe Meng

Short Bio

Dr. Meng received the B.S. and Ph.D. degrees from Xidian University, Xi'an, China, in 2014 and 2020, respectively, under the supervision of Prof. Licheng Jiao. He is currently a Lecturer with the School of Telecommunication and Information Engineering, Xi'an University of Posts and Telecommunications. His research interests include deep learning and hyperspectral image classification.

Publications

Journals:

[1]. 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, Early Access, doi: 10.1109/LGRS.2021.3069202.（中科院二区, IF:5.343）
[2]. Zhe Meng*, Feng Zhao, Miaomiao Liang, and Wen Xie. Deep residual involution network for hyperspectral image classification[J]. Remote Sensing, 2021, 13(16): 3055.（中科院二区Top, IF:5.349）
[3]. 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.（中科院二区, IF:4.715）
[4]. 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.（中科院二区Top, IF:5.349）
[5]. 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.（中科院二区Top, IF:5.349）
[6]. 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.（中科院二区Top, IF:5.349）
[7]. 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, Accepted.（SCI二区, IF:5.343）
[8]. 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.（中科院二区Top, IF:5.349）
[9]. 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.（中科院二区Top, IF:5.349）
[10]. 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. （中科院二区Top, IF:5.349）
[11]. 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.（中科院二区Top, IF:5.349）

Conferences

[1]. 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), 2022, Accepted. (EI)