World's Best Scientists 2026 revealed!
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Rising Stars
2025

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Rising Stars

D-Index
45
Citations
12430
World Ranking
436
National Ranking
12

Computer Science

D-Index
46
Citations
9311
World Ranking
6814
National Ranking
324

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Lichao Mou is affiliated with the Technical University of Munich in Germany. Their research focuses primarily on computer science and engineering, with significant contributions in subfields including computer vision and pattern recognition, media technology, artificial intelligence, atmospheric science, and aerospace engineering.

The research topics covered by Lichao Mou include:

  • Remote-Sensing Image Classification
  • Advanced Image and Video Retrieval Techniques
  • Domain Adaptation and Few-Shot Learning
  • Video Surveillance and Tracking Methods
  • Multimodal Machine Learning Applications
  • Automated Road and Building Extraction
  • Advanced Neural Network Applications

Lichao Mou has published extensively in various scientific venues. The most frequent publication venues are:

  • IEEE Transactions on Geoscience and Remote Sensing
  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • International Journal of Applied Earth Observation and Geoinformation
  • IEEE Geoscience and Remote Sensing Magazine

Some of their recent papers include:

  • Nonlocal Graph Convolutional Networks for Hyperspectral Image Classification, 2020, IEEE Transactions on Geoscience and Remote Sensing
  • Relation Matters: Relational Context-Aware Fully Convolutional Network for Semantic Segmentation of High-Resolution Aerial Images, 2020, IEEE Transactions on Geoscience and Remote Sensing

Other notable papers relevant to their field of study, though authored by collaborators, include:

  • Deep Learning Meets SAR: Concepts, models, pitfalls, and perspectives, 2021, IEEE Geoscience and Remote Sensing Magazine
  • Self-Supervised Learning in Remote Sensing: A review, 2022, IEEE Geoscience and Remote Sensing Magazine
  • Bi-Temporal Semantic Reasoning for the Semantic Change Detection in HR Remote Sensing Images, 2022, IEEE Transactions on Geoscience and Remote Sensing

Lichao Mou frequently collaborates with a number of researchers, including:

  • Xiao Xiang Zhu
  • Yuansheng Hua
  • Yilei Shi
  • Konrad Heidler
  • Jingliang Hu

Best Publications

  • Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources

    Xiao Xiang Zhu;Devis Tuia;Lichao Mou;Gui-Song Xia

  • Deep learning in remote sensing: a review

    Xiao Xiang Zhu;Devis Tuia;Lichao Mou;Gui-Song Xia

  • Deep Recurrent Neural Networks for Hyperspectral Image Classification

    Unknown

  • Learning Spectral-Spatial-Temporal Features via a Recurrent Convolutional Neural Network for Change Detection in Multispectral Imagery

    Lichao Mou;Lorenzo Bruzzone;Xiao Xiang Zhu

  • Self-Supervised Learning in Remote Sensing: A review

    Unknown

  • Learning a Transferable Change Rule from a Recurrent Neural Network for Land Cover Change Detection

    Haobo Lyu;Hui Lu;Lichao Mou

  • Unsupervised Spectral–Spatial Feature Learning via Deep Residual Conv–Deconv Network for Hyperspectral Image Classification

    Lichao Mou;Pedram Ghamisi;Xiao Xiang Zhu

  • Deep Learning Meets SAR: Concepts, Models, Pitfalls, and Perspectives

    Xiaoxiang Zhu;Sina Montazeri;Mohsin Ali;Yuansheng Hua

  • Nonlocal Graph Convolutional Networks for Hyperspectral Image Classification

    Lichao Mou;Xiaoqiang Lu;Xuelong Li;Xiao Xiang Zhu

  • Identifying Corresponding Patches in SAR and Optical Images With a Pseudo-Siamese CNN

    Lloyd H. Hughes;Michael Schmitt;Lichao Mou;Yuanyuan Wang

  • Scene Recognition by Manifold Regularized Deep Learning Architecture

    Yuan Yuan;Lichao Mou;Xiaoqiang Lu

  • Learning Spectral-Spatial-Temporal Features via a Recurrent Convolutional Neural Network for Change Detection in Multispectral Imagery

    Lichao Mou;Lorenzo Bruzzone;Xiao Xiang Zhu

  • Learning to Pay Attention on Spectral Domain: A Spectral Attention Module-Based Convolutional Network for Hyperspectral Image Classification

    Lichao Mou;Xiao Xiang Zhu

  • HSF-Net: Multiscale Deep Feature Embedding for Ship Detection in Optical Remote Sensing Imagery

    Qingpeng Li;Lichao Mou;Qingjie Liu;Yunhong Wang

  • A Relation-Augmented Fully Convolutional Network for Semantic Segmentation in Aerial Scenes

    Lichao Mou;Yuansheng Hua;Xiao Xiang Zhu

  • Bi-Temporal Semantic Reasoning for the Semantic Change Detection in HR Remote Sensing Images

    Lei Ding;Haitao Guo;Sicong Liu;Lichao Mou

  • Semi-Supervised Multitask Learning for Scene Recognition

    Xiaoqiang Lu;Xuelong Li;Lichao Mou

  • Recurrently exploring class-wise attention in a hybrid convolutional and bidirectional LSTM network for multi-label aerial image classification.

    Yuansheng Hua;Yuansheng Hua;Lichao Mou;Lichao Mou;Xiao Xiang Zhu;Xiao Xiang Zhu

  • Relation Matters: Relational Context-Aware Fully Convolutional Network for Semantic Segmentation of High-Resolution Aerial Images

    Lichao Mou;Yuansheng Hua;Xiao Xiang Zhu

  • HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline

    Konrad Heidler;Lichao Mou;Celia Baumhoer;Andreas Dietz

  • Vehicle Instance Segmentation From Aerial Image and Video Using a Multitask Learning Residual Fully Convolutional Network

    Lichao Mou;Xiao Xiang Zhu

  • Local climate zone-based urban land cover classification from multi-seasonal Sentinel-2 images with a recurrent residual network.

    Chunping Qiu;Lichao Mou;Lichao Mou;Michael Schmitt;Xiao Xiang Zhu;Xiao Xiang Zhu

  • HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline

    Konrad Heidler;Lichao Mou;Celia A. Baumhoer;Andreas J. Dietz

  • An Unsupervised Remote Sensing Change Detection Method Based on Multiscale Graph Convolutional Network and Metric Learning

    Xu Tang;Huayu Zhang;Lichao Mou;Fang Liu

  • So2Sat LCZ42: A Benchmark Data Set for the Classification of Global Local Climate Zones [Software and Data Sets]

    Xiao Xiang Zhu;Jingliang Hu;Chunping Qiu;Yilei Shi

  • IM2HEIGHT: Height Estimation from Single Monocular Imagery via Fully Residual Convolutional-Deconvolutional Network.

    Lichao Mou;Xiao Xiang Zhu

Frequent Co-Authors

Xiao Xiang Zhu
Xiao Xiang Zhu Technical University of Munich
Lorenzo Bruzzone
Lorenzo Bruzzone University of Trento
Xiaoqiang Lu
Xiaoqiang Lu Chinese Academy of Sciences
Devis Tuia
Devis Tuia École Polytechnique Fédérale de Lausanne
Francesca Bovolo
Francesca Bovolo Fondazione Bruno Kessler
Pedram Ghamisi
Pedram Ghamisi Helmholtz-Zentrum Dresden-Rossendorf
Xuelong Li
Xuelong Li China Telecom (China)
Feng Xu
Feng Xu Fudan University
Z. Jane Wang
Z. Jane Wang University of British Columbia
Hui Lu
Hui Lu Tsinghua University

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