Xinghua Li

Xinghua Li

Wuhan University

H-index: 27

Asia-China

About Xinghua Li

Xinghua Li, With an exceptional h-index of 27 and a recent h-index of 26 (since 2020), a distinguished researcher at Wuhan University, specializes in the field of image processing, multitemporal remote sensing, change detection, cloud removal, deep learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

A remote sensing assessment index for urban ecological livability and its application

Spatiotemporal Enhancement and Interlevel Fusion Network for Remote Sensing Images Change Detection

Global and Local Dual Fusion Network for Large-ratio Cloud Occlusion Missing Information Reconstruction of a High-resolution Remote Sensing Image

Residual Dual U-shape Networks With Improved Skip Connections for Cloud Detection

Remote Sensing Image Destriping using Weighted Low-rank Prior and Global Spatial–Spectral Total Variation

Concatenated Deep Learning Framework for Multi-task Change Detection of Optical and SAR Images

Large-scale land use/land cover extraction from Landsat imagery using feature relationships matrix based deep-shallow learning

数据融合视角下的遥感参量空间降尺度

Xinghua Li Information

University

Position

Associate Professor School of Remote Sensing and Information Engineering

Citations(all)

3410

Citations(since 2020)

3114

Cited By

1128

hIndex(all)

27

hIndex(since 2020)

26

i10Index(all)

40

i10Index(since 2020)

38

Email

University Profile Page

Wuhan University

Google Scholar

View Google Scholar Profile

Xinghua Li Skills & Research Interests

image processing

multitemporal remote sensing

change detection

cloud removal

deep learning

Top articles of Xinghua Li

Title

Journal

Author(s)

Publication Date

A remote sensing assessment index for urban ecological livability and its application

Geo-Spatial Information Science

Junbo Yu

Xinghua Li

Xiaobin Guan

Huanfeng Shen

2024

Spatiotemporal Enhancement and Interlevel Fusion Network for Remote Sensing Images Change Detection

IEEE Transactions on Geoscience and Remote Sensing

Yanyuan Huang

Xinghua Li

Zhengshun Du

Huanfeng Shen

2024/2/2

Global and Local Dual Fusion Network for Large-ratio Cloud Occlusion Missing Information Reconstruction of a High-resolution Remote Sensing Image

IEEE Geoscience and Remote Sensing Letters

Weiling Liu

Yonghua Jiang

Jingyin Wang

Guo Zhang

Da Li

...

2024/1/26

Residual Dual U-shape Networks With Improved Skip Connections for Cloud Detection

IEEE Geoscience and Remote Sensing Letters

Ao Li

Xinghua Li

Xiaoshuang Ma

2024/1

Remote Sensing Image Destriping using Weighted Low-rank Prior and Global Spatial–Spectral Total Variation

Journal of Imaging Science and Technology

Zhiyong Zuo

Zhongjian Wu

Zhenbao Luo

Yuyong Cui

Xinghua Li

...

2024/11/1

Concatenated Deep Learning Framework for Multi-task Change Detection of Optical and SAR Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Zhengshun Du

Xinghua Li

Jianhao Miao

Yanyuan Huang

Huanfeng Shen

...

2024

Large-scale land use/land cover extraction from Landsat imagery using feature relationships matrix based deep-shallow learning

International Journal of Applied Earth Observation and Geoinformation

Peng Dou

Huanfeng Shen

Chunlin Huang

Zhiwei Li

Yujun Mao

...

2024/5/1

数据融合视角下的遥感参量空间降尺度

武汉大学学报 (信息科学版)

景映红, 沈焕锋, 李星华, 吴金橄, 邱中航

2024

Enhanced wavelet based spatiotemporal fusion networks using cross-paired remote sensing images

ISPRS Journal of Photogrammetry and Remote Sensing

Xingjian Zhang

Shuang Li

Zhenyu Tan

Xinghua Li

2024/5/1

Detail Injection-based Spatio-Temporal Fusion for Remote Sensing Images with Land Cover Changes

IEEE Transactions on Geoscience and Remote Sensing

Qiang Liu

Xiangchao Meng

Xinghua Li

Feng Shao

2023/3/6

A Cross-Paired Wavelet Based Spatiotemporal Fusion Network for Remote Sensing Images

Xingjian Zhang

Shaohuai Yu

Xinghua Li

Shuang Li

Zhenyu Tan

2023/9/22

Monitoring vegetation dynamics (2010–2020) in Shengnongjia Forestry District with cloud-removed MODIS NDVI series by a spatio-temporal reconstruction method

The Egyptian Journal of Remote Sensing and Space Science

Shuang Li

Liang Xu

Jiajia Chen

Yazhen Jiang

Shuying Sun

...

2023/12/1

Bishift Networks for Thick Cloud Removal with Multitemporal Remote Sensing Images

International Journal of Intelligent Systems

Chaojun Long

Xinghua Li

Yinghong Jing

Huanfeng Shen

2023/2/21

A global+ multiscale hybrid network for hyperspectral image classification

Remote Sensing Letters

Anqi Zhao

Ce Wang

Xinghua Li

2023/9/2

A GAN-based Relative Radiometric Correction Model of Remote Sensing Data

Linglin Xie

Jianhao Miao

Xinghua Li

Xuechen Bai

Kaijun Yang

2023/10/20

遥感影像深度学习配准方法综述

遥感学报

李星华, 艾文浩, 冯蕊涛, 罗少杰

2023/2

基于主题模型的城市地块活动语义动态提取

遥感技术与应用

肖锐, 郭宇翔, 李星华

2023/7

DecRecNet: A Decoupling-Reconstruction Network for Restoring the Missing Information of Optical Remote Sensing Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Weiling Liu

Hao Cui

Yonghua Jiang

Guo Zhang

Xinghua Li

...

2023/10/27

Combing remote sensing information entropy and machine learning for ecological environment assessment of Hefei-Nanjing-Hangzhou region, China

Journal of Environmental Management

Hongyi Zhang

Yong Liu

Xinghua Li

Ruitao Feng

Yuting Gong

...

2023/1/1

Dual-channel parallel hybrid convolutional neural networks based classification method for high-resolution remote sensing image

Acta Geodaetica et Cartographica Sinica

Xiaohu Gu

Zhengjun Li

Jianhao Miao

Xinghua Li

Huanfeng Shen

2023/5

See List of Professors in Xinghua Li University(Wuhan University)

Co-Authors

H-index: 128
zhang liangpei

zhang liangpei

Wuhan University

H-index: 105
Jing M Chen

Jing M Chen

University of Toronto

H-index: 72
Huanfeng Shen

Huanfeng Shen

Wuhan University

H-index: 51
Qiangqiang Yuan

Qiangqiang Yuan

Wuhan University

H-index: 44
Hongyan Zhang

Hongyan Zhang

Wuhan University

H-index: 37
Frank Göttsche

Frank Göttsche

Karlsruher Institut für Technologie

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