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Qiangqiang Yuan

Qiangqiang Yuan

D-Index & Metrics

Computer Science

D-Index
59
Citations
13690
World Ranking
3431
National Ranking
461

Overview

Qiangqiang Yuan is affiliated with Wuhan University in China. Their research primarily focuses on environmental science, engineering, and computer science, with significant contributions in subfields including computer vision and pattern recognition, media technology, atmospheric science, environmental engineering, and global and planetary change.

The main topics covered in Yuan's work involve advanced image fusion techniques, image and signal denoising methods, advanced image processing techniques, remote-sensing image classification, air quality monitoring and forecasting, atmospheric and environmental gas dynamics, and atmospheric chemistry and aerosols.

Yuan has authored several recent notable papers, such as:

  • Deep learning in environmental remote sensing: Achievements and challenges (2020), published in Remote Sensing of Environment
  • TTST: A Top-k Token Selective Transformer for Remote Sensing Image Super-Resolution (2024), published in IEEE Transactions on Image Processing
  • EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution (2023), published in IEEE Transactions on Geoscience and Remote Sensing
  • From degrade to upgrade: Learning a self-supervised degradation guided adaptive network for blind remote sensing image super-resolution (2023), published in Information Fusion
  • Thick cloud and cloud shadow removal in multitemporal imagery using progressively spatio-temporal patch group deep learning (2020), published in ISPRS Journal of Photogrammetry and Remote Sensing

Throughout their career, Yuan has collaborated frequently with:

  • Liangpei Zhang
  • Huanfeng Shen
  • Jie Li
  • Jiang He
  • Yuan Wang

Yuan's work has been published extensively in venues such as:

  • IEEE Transactions on Geoscience and Remote Sensing
  • Zenodo (CERN European Organization for Nuclear Research)
  • ISPRS Journal of Photogrammetry and Remote Sensing
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • International Journal of Applied Earth Observation and Geoinformation

The research output reflects a continuous focus on remote sensing and advanced computational methods applied to environmental and atmospheric data. Yuan's work demonstrates engagement with image super-resolution, deep learning approaches, and spatio-temporal analysis techniques aimed at addressing challenges in environmental monitoring and data processing.

Best Publications

  • Deep learning in environmental remote sensing: Achievements and challenges

    Qiangqiang Yuan;Huanfeng Shen;Tongwen Li;Zhiwei Li

  • Hyperspectral Image Restoration Using Low-Rank Matrix Recovery

    Hongyan Zhang;Wei He;Liangpei Zhang;Huanfeng Shen

  • Hyperspectral Image Denoising Employing a Spectral–Spatial Adaptive Total Variation Model

    Qiangqiang Yuan;Liangpei Zhang;Huanfeng Shen

  • Image super-resolution

    Linwei Yue;Huanfeng Shen;Jie Li;Qiangqiang Yuan

  • A Multiscale and Multidepth Convolutional Neural Network for Remote Sensing Imagery Pan-Sharpening

    Qiangqiang Yuan;Yancong Wei;Xiangchao Meng;Huanfeng Shen

  • Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach

    Tongwen Li;Huanfeng Shen;Qiangqiang Yuan;Xuechen Zhang

  • Boosting the Accuracy of Multispectral Image Pansharpening by Learning a Deep Residual Network

    Yancong Wei;Qiangqiang Yuan;Huanfeng Shen;Liangpei Zhang

  • Missing Data Reconstruction in Remote Sensing Image With a Unified Spatial–Temporal–Spectral Deep Convolutional Neural Network

    Qiang Zhang;Qiangqiang Yuan;Chao Zeng;Xinghua Li

  • TTST: A Top-k Token Selective Transformer for Remote Sensing Image Super-Resolution

    Unknown

  • Recovering Quantitative Remote Sensing Products Contaminated by Thick Clouds and Shadows Using Multitemporal Dictionary Learning

    Xinghua Li;Huanfeng Shen;Liangpei Zhang;Hongyan Zhang

  • Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network.

    Qiangqiang Yuan;Qiang Zhang;Jie Li;Huanfeng Shen

  • From degrade to upgrade: Learning a self-supervised degradation guided adaptive network for blind remote sensing image super-resolution

    Unknown

  • Learning a Dilated Residual Network for SAR Image Despeckling

    Qiang Zhang;Qiangqiang Yuan;Jie Li;Zhen Yang

  • An effective thin cloud removal procedure for visible remote sensing images

    Huanfeng Shen;Huifang Li;Yan Qian;Liangpei Zhang

  • Point-surface fusion of station measurements and satellite observations for mapping PM2.5 distribution in China: Methods and assessment

    Tongwen Li;Huanfeng Shen;Chao Zeng;Qiangqiang Yuan

  • EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution

    Unknown

  • Cloud removal for remotely sensed images by similar pixel replacement guided with a spatio-temporal MRF model

    Qing Cheng;Huanfeng Shen;Liangpei Zhang;Qiangqiang Yuan

  • Multiframe Super-Resolution Employing a Spatially Weighted Total Variation Model

    Qiangqiang Yuan;Liangpei Zhang;Huanfeng Shen

  • Hyperspectral Image Restoration via Iteratively Regularized Weighted Schatten $p$ -Norm Minimization

    Yuan Xie;Yanyun Qu;Dacheng Tao;Weiwei Wu

  • Hyperspectral Image Denoising Employing a Spatial–Spectral Deep Residual Convolutional Neural Network

    Qiangqiang Yuan;Qiang Zhang;Jie Li;Huanfeng Shen

  • Thick cloud and cloud shadow removal in multitemporal imagery using progressively spatio-temporal patch group deep learning

    Qiang Zhang;Qiangqiang Yuan;Jie Li;Zhiwei Li

  • Cloud Removal with Fusion of High Resolution Optical and SAR Images Using Generative Adversarial Networks

    Jianhao Gao;Qiangqiang Yuan;Jie Li;Hai Zhang

  • Space-time super-resolution for satellite video: A joint framework based on multi-scale spatial-temporal transformer

    Unknown

  • NTIRE 2022 Spectral Recovery Challenge and Data Set

    Unknown

  • A Large-Scale Benchmark Data Set for Evaluating Pansharpening Performance: Overview and Implementation

    Xiangchao Meng;Yiming Xiong;Feng Shao;Huanfeng Shen

  • Hybrid Noise Removal in Hyperspectral Imagery With a Spatial–Spectral Gradient Network

    Qiang Zhang;Qiangqiang Yuan;Jie Li;Xinxin Liu

  • High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations

    Linwei Yue;Huanfeng Shen;Liangpei Zhang;Xianwei Zheng

  • Satellite Video Super-Resolution via Multiscale Deformable Convolution Alignment and Temporal Grouping Projection

    Yi Xiao;Xin Su;Qiangqiang Yuan;Denghong Liu

Frequent Co-Authors

Huanfeng Shen
Huanfeng Shen Wuhan University
Liangpei Zhang
Liangpei Zhang Wuhan University
Hongyan Zhang
Hongyan Zhang China University of Geosciences
Michael K. Ng
Michael K. Ng Hong Kong Baptist University
Zhiwei Li
Zhiwei Li Central South University
Pingxiang Li
Pingxiang Li Wuhan University
Dacheng Tao
Dacheng Tao Nanyang Technological University
Zhanqing Li
Zhanqing Li University of Maryland, College Park
Maureen Cribb
Maureen Cribb University of Maryland, College Park
Yuan Xie
Yuan Xie Hong Kong University of Science and Technology

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