3.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Liangpei Zhang3 profiles44 · h 130
- Gui-Song Xia2 profiles22 · h 43
- Huanfeng Shen19 · h 76
- Qiangqiang Yuan15 · h 59
- Bo Du2 profiles11 · h 82
- Chen Wu3 profiles11 · h 29
- Guisong Xia2 profiles11 · h 39
- Chenxi Duan2 profiles9 · h 19
- L. Zhang9 · h 59
- Rui Li2 profiles8 · h 15
- Ce Zhang2 profiles7 · h 28
- Jie Li7 · h 26
- Wuhan UniversityCN150 papers
- Chinese Academy of SciencesCN13 papers
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)DE9 papers
- Huazhong University of Science and TechnologyCN8 papers
- Technical University of MunichDE8 papers
- China University of GeosciencesCN7 papers
- Lancaster UniversityGB7 papers
- UK Centre for Ecology & HydrologyGB7 papers
- The University of TokyoJP6 papers
- Sun Yat-sen UniversityCN5 papers
- University of SouthamptonGB5 papers
- Institute of Geographic Sciences and Natural Resources ResearchCN4 papers
28 papers · 1 filter
Spectral Response Function Guided Deep Optimization-driven Network for Spectral Super-resolution
Jiang He, Jie Li, Qiangqiang Yuan +2
Hyperspectral images are crucial for many research works. Spectral super-resolution (SSR) is a method used to obtain high spatial resolution (HR) hyperspectral images from HR multi…
FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware Modelling
Kangcheng Liu, Zhi Gao, Feng Lin +1
This work presents FG-Net, a general deep learning framework for large-scale point clouds understanding without voxelizations, which achieves accurate and real-time performance wit…
Multi-stage Attention ResU-Net for Semantic Segmentation of Fine-Resolution Remote Sensing Images
Rui Li, Shunyi Zheng, Chenxi Duan +2
The attention mechanism can refine the extracted feature maps and boost the classification performance of the deep network, which has become an essential technique in computer visi…
Decoding PPP Corrections from BDS B2b Signals Using a Software-defined Receiver: an Initial Performance Evaluation
Xiangchen Lu, Liang Chen, Nan Shen +3
With the rapid development of China's BeiDou Navigation Satellite System(BDS), the application of real-time precise point positioning (RTPPP) based on BDS has become an active rese…
FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification
Zhuo Zheng, Yanfei Zhong, Ailong Ma +1
Deep learning techniques have provided significant improvements in hyperspectral image (HSI) classification. The current deep learning based HSI classifiers follow a patch-based le…
Spatiotemporal Differences of COVID-19 Infection among Healthcare Workers and Patients in China from January to March 2020
Peixiao Wang, Xinyan Zhu, Wei Guo +2
Studying the spatiotemporal differences in coronavirus disease (COVID-19) between social groups such as healthcare workers (HCWs) and patients can aid in formulating epidemic conta…
Exploring the impact of under-reported cases on the COVID-19 spatiotemporal distribution using healthcare worker infection data
Peixiao Wang, Tao Hu, Hongqiang Liu +1
A timely understanding of the spatiotemporal pattern and development trend of COVID-19 is critical for timely prevention and control. However, the under-reporting of cases is wides…
A Simple and Efficient Registration of 3D Point Cloud and Image Data for Indoor Mobile Mapping System
Hao Ma, Jingbin Liu, Keke Liu +5
Registration of 3D LiDAR point clouds with optical images is critical in the combination of multi-source data. Geometric misalignment originally exists in the pose data between LiD…
HCNet: Hierarchical Context Network for Semantic Segmentation
Yanwen Chong, Congchong Nie, Yulong Tao +2
Global context information is vital in visual understanding problems, especially in pixel-level semantic segmentation. The mainstream methods adopt the self-attention mechanism to…
Few-Shot Hyperspectral Image Classification With Unknown Classes Using Multitask Deep Learning
Shengjie Liu, Qian Shi, Liangpei Zhang
Current hyperspectral image classification assumes that a predefined classification system is closed and complete, and there are no unknown or novel classes in the unseen data. How…
Multi-Attention-Network for Semantic Segmentation of Fine Resolution Remote Sensing Images
Rui Li, Shunyi Zheng, Chenxi Duan +3
Semantic segmentation of remote sensing images plays an important role in a wide range of applications including land resource management, biosphere monitoring and urban planning.…
Thick Cloud Removal of Remote Sensing Images Using Temporal Smoothness and Sparsity-Regularized Tensor Optimization
Chenxi Duan, Jun Pan, Rui Li
In remote sensing images, the presence of thick cloud accompanying cloud shadow is a high probability event, which can affect the quality of subsequent processing and limit the sce…
Formulation to test gravitational redshift based on the tri-frequency combination of ACES frequency links
Xiao Sun, Wen-Bin Shen, Ziyu Shen +3
Atomic Clock Ensemble in Space (ACES) is an ESA mission mainly designed to test gravitational redshift with high-performance atomic clocks in space and on the ground. A crucial par…
Land Cover Classification from Remote Sensing Images Based on Multi-Scale Fully Convolutional Network
Rui Li, Shunyi Zheng, Chenxi Duan +1
In this paper, a Multi-Scale Fully Convolutional Network (MSFCN) with multi-scale convolutional kernel is proposed to exploit discriminative representations from two-dimensional (2…
X-ModalNet: A Semi-Supervised Deep Cross-Modal Network for Classification of Remote Sensing Data
Danfeng Hong, Naoto Yokoya, Gui-Song Xia +2
This paper addresses the problem of semi-supervised transfer learning with limited cross-modality data in remote sensing. A large amount of multi-modal earth observation images, su…
MACU-Net for Semantic Segmentation of Fine-Resolution Remotely Sensed Images
Rui Li, Chenxi Duan, Shunyi Zheng +2
Semantic segmentation of remotely sensed images plays an important role in land resource management, yield estimation, and economic assessment. U-Net, a deep encoder-decoder archit…
Multi-Temporal Scene Classification and Scene Change Detection with Correlation based Fusion
Lixiang Ru, Bo Du, Chen Wu
Classifying multi-temporal scene land-use categories and detecting their semantic scene-level changes for imagery covering urban regions could straightly reflect the land-use trans…
Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion
Yujin Chen, Zhigang Tu, Di Kang +4
Accurate 3D reconstruction of the hand and object shape from a hand-object image is important for understanding human-object interaction as well as human daily activities. Differen…
On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AID
Yang Long, Gui-Song Xia, Shengyang Li +5
The past years have witnessed great progress on remote sensing (RS) image interpretation and its wide applications. With RS images becoming more accessible than ever before, there…
3D Face Anti-spoofing with Factorized Bilinear Coding
Shan Jia, Xin Li, Chuanbo Hu +2
We have witnessed rapid advances in both face presentation attack models and presentation attack detection (PAD) in recent years. When compared with widely studied 2D face presenta…
Towards Robust Crowdsourcing-Based Localization: A Fingerprinting Accuracy Indicator Enhanced Wireless/Magnetic/Inertial Integration Approach
You Li, Zhe He, Zhouzheng Gao +3
The next-generation internet of things (IoT) systems have an increasingly demand on intelligent localization which can scale with big data without human perception. Thus, tradition…
Deep Reinforcement Learning (DRL): Another Perspective for Unsupervised Wireless Localization
You Li, Xin Hu, Yuan Zhuang +3
Location is key to spatialize internet-of-things (IoT) data. However, it is challenging to use low-cost IoT devices for robust unsupervised localization (i.e., localization without…
Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation
You Li, Yuan Zhuang, Xin Hu +12
The Internet of Things (IoT) has started to empower the future of many industrial and mass-market applications. Localization techniques are becoming key to add location context to…
Forecast Network-Wide Traffic States for Multiple Steps Ahead: A Deep Learning Approach Considering Dynamic Non-Local Spatial Correlation and Non-Stationary Temporal Dependency
Xinglei Wang, Xuefeng Guan, Jun Cao +2
Obtaining accurate information about future traffic flows of all links in a traffic network is of great importance for traffic management and control applications. This research st…