World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
84
Citations
25554
World Ranking
863
National Ranking
130

Overview

Bo Du is a researcher affiliated with Wuhan University in China, with a substantial body of work spanning computer science and engineering. Their research primarily focuses on computer vision and pattern recognition as well as artificial intelligence. They have a notable presence in media technology, atmospheric science, and medical imaging related to radiology, nuclear medicine, and imaging.

Bo Du's research interests include topics such as remote-sensing image classification, domain adaptation and few-shot learning, remote sensing and land use, advanced image and video retrieval techniques, advanced neural network applications, advanced image fusion techniques, and advanced graph neural networks. These areas reflect a broad engagement with both theoretical and applied aspects of computer vision and machine learning.

The researcher has published extensively in various reputable venues, with frequent publications in:

  • arXiv (Cornell University)
  • IEEE Transactions on Geoscience and Remote Sensing
  • IEEE Transactions on Image Processing
  • Neural Networks
  • Zenodo (CERN European Organization for Nuclear Research)

Bo Du has collaborated with multiple coauthors on numerous publications. Their frequent collaborators include Liangpei Zhang, Dacheng Tao, Mang Ye, Chen Wu, and Juhua Liu. These collaborations likely contribute to their interdisciplinary approach within computer vision and remote sensing domains.

Among Bo Du's recent papers are:

  • Heterogeneous Federated Learning: State-of-the-art and Research Challenges (2023), ACM Computing Surveys
  • Channel Augmented Joint Learning for Visible-Infrared Recognition (2021), 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Learning Affinity from Attention: End-to-End Weakly-Supervised Semantic Segmentation with Transformers (2022), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Dimensionality Reduction With Enhanced Hybrid-Graph Discriminant Learning for Hyperspectral Image Classification (2020), IEEE Transactions on Geoscience and Remote Sensing
  • Advancing Plain Vision Transformer Toward Remote Sensing Foundation Model (2022), IEEE Transactions on Geoscience and Remote Sensing

Bo Du's work contributes broadly to advancing methodologies in remote sensing image classification and the integration of machine learning techniques into geoscience and multimedia technologies. Their research includes significant developments in federated learning, semantic segmentation, hyperspectral image classification, and joint learning approaches for visible-infrared recognition.

Best Publications

  • Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art

    Liangpei Zhang;Lefei Zhang;Bo Du

  • Saliency-Guided Unsupervised Feature Learning for Scene Classification

    Fan Zhang;Bo Du;Liangpei Zhang

  • Multiscale Dynamic Graph Convolutional Network for Hyperspectral Image Classification

    Sheng Wan;Chen Gong;Ping Zhong;Bo Du

  • Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images

    Bo Du;Lixiang Ru;Chen Wu;Liangpei Zhang

  • A Low-Rank and Sparse Matrix Decomposition-Based Mahalanobis Distance Method for Hyperspectral Anomaly Detection

    Yuxiang Zhang;Bo Du;Liangpei Zhang;Shugen Wang

  • Scene Classification via a Gradient Boosting Random Convolutional Network Framework

    Fan Zhang;Bo Du;Liangpei Zhang

  • Stacked Convolutional Denoising Auto-Encoders for Feature Representation

    Bo Du;Wei Xiong;Jia Wu;Lefei Zhang

  • Recurrent Feature Reasoning for Image Inpainting

    Jingyuan Li;Ning Wang;Lefei Zhang;Bo Du

  • Unsupervised Domain Adaptive Re-Identification: Theory and Practice

    Liangchen Song;Cheng Wang;Lefei Zhang;Bo Du

  • Slow Feature Analysis for Change Detection in Multispectral Imagery

    Chen Wu;Bo Du;Liangpei Zhang

  • Random-Selection-Based Anomaly Detector for Hyperspectral Imagery

    Bo Du;Liangpei Zhang

  • Change Detection in Multisource VHR Images via Deep Siamese Convolutional Multiple-Layers Recurrent Neural Network

    Hongruixuan Chen;Chen Wu;Bo Du;Liangpei Zhang

  • Spectral–Spatial Unified Networks for Hyperspectral Image Classification

    Yonghao Xu;Liangpei Zhang;Bo Du;Fan Zhang

  • Advanced Multi-Sensor Optical Remote Sensing for Urban Land Use and Land Cover Classification: Outcome of the 2018 IEEE GRSS Data Fusion Contest

    Yonghao Xu;Bo Du;Liangpei Zhang;Daniele Cerra

  • Ensemble manifold regularized sparse low-rank approximation for multiview feature embedding

    Lefei Zhang;Qian Zhang;Liangpei Zhang;Dacheng Tao

  • Feature Learning Using Spatial-Spectral Hypergraph Discriminant Analysis for Hyperspectral Image

    Fulin Luo;Bo Du;Liangpei Zhang;Lefei Zhang

  • A Discriminative Metric Learning Based Anomaly Detection Method

    Bo Du;Liangpei Zhang

  • Weakly Supervised Learning Based on Coupled Convolutional Neural Networks for Aircraft Detection

    Fan Zhang;Bo Du;Liangpei Zhang;Miaozhong Xu

  • A post-classification change detection method based on iterative slow feature analysis and Bayesian soft fusion

    Chen Wu;Bo Du;Xiaohui Cui;Liangpei Zhang

  • Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.

    Lefei Zhang;Qian Zhang;Bo Du;Xin Huang

  • Hyperspectral image unsupervised classification by robust manifold matrix factorization

    Lefei Zhang;Liangpei Zhang;Bo Du;Jane You

Frequent Co-Authors

Liangpei Zhang
Liangpei Zhang Wuhan University
Lefei Zhang
Lefei Zhang Wuhan University
Dacheng Tao
Dacheng Tao Nanyang Technological University
Jia Wu
Jia Wu Macquarie University
Pingkun Yan
Pingkun Yan Rensselaer Polytechnic Institute
Chang Xu
Chang Xu University of Sydney
Xuelong Li
Xuelong Li China Telecom (China)
Jane You
Jane You Hong Kong Polytechnic University
Ting Wang
Ting Wang Washington University in St. Louis
Shirui Pan
Shirui Pan Griffith University

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