Bo Du
Impact in
- Media Technology top 0.01%
- Remote-Sensing Image Classification
- Advanced Image Fusion Techniques
- Computer Vision and Pattern Recognition top 0.05%
- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Generative Adversarial Networks and Image Synthesis
Papers in
- Media Technology 260
- Remote-Sensing Image Classification 260
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- Advanced Neural Network Applications 53
- Video Surveillance and Tracking Methods 48
- Medical Image Segmentation Techniques 28
- Generative Adversarial Networks and Image Synthesis 21
- Co-authors
- Liangpei Zhang (202 shared papers)Lefei Zhang (108 shared papers)Dacheng Tao (105 shared papers)Chen Wu (57 shared papers)Fan Zhang (7 shared papers)Mang Ye (50 shared papers)Yonghao Xu (17 shared papers)Yuxiang Zhang (34 shared papers)
- Journals
- IEEE Transactions on Geoscience and Remote Sensing (109 papers)IEEE Transactions on Image Processing (42 papers)IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (31 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (24 papers)Pattern Recognition (22 papers)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Bo Du
660 papers receiving 27.8k citations
Bo Du's Hit Papers
Peers
Comparison fields: 5 of 164
- Media Technology 13.8k
- Computer Vision and Pattern Recognition 7.4k
- Computational Mathematics 193
- Artificial Intelligence 4.3k
- Ocean Engineering 883
Countries citing papers authored by Bo Du
This map shows the geographic impact of Bo Du's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bo Du with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bo Du more than expected).
Fields of papers citing papers by Bo Du
This network shows the impact of papers produced by Bo Du. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bo Du. The network helps show where Bo Du may publish in the future.
Co-authors
The 25 scholars most cited alongside Bo Du, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 749 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art Hit paper breakdown → | 2016 | 1833 |
| 2 | Saliency-Guided Unsupervised Feature Learning for Scene Classification Hit paper breakdown → | 2014 | 488 |
| 3 | Multiscale Dynamic Graph Convolutional Network for Hyperspectral Image Classification Hit paper breakdown → | 2019 | 476 |
| 4 | Weighted Feature Fusion of Convolutional Neural Network and Graph Attention Network for Hyperspectral Image Classification Hit paper breakdown → | 2022 | 450 |
| 5 | A Low-Rank and Sparse Matrix Decomposition-Based Mahalanobis Distance Method for Hyperspectral Anomaly Detection Hit paper breakdown → | 2015 | 438 |
| 6 | Scene Classification via a Gradient Boosting Random Convolutional Network Framework Hit paper breakdown → | 2015 | 385 |
| 7 | Recurrent Feature Reasoning for Image Inpainting Hit paper breakdown → | 2020 | 364 |
| 8 | Stacked Convolutional Denoising Auto-Encoders for Feature Representation Hit paper breakdown → | 2016 | 354 |
| 9 | Heterogeneous Federated Learning: State-of-the-art and Research Challenges Hit paper breakdown → | 2023 | 343 |
| 10 | Change Detection in Multisource VHR Images via Deep Siamese Convolutional Multiple-Layers Recurrent Neural Network Hit paper breakdown → | 2019 | 303 |
| 11 | Slow Feature Analysis for Change Detection in Multispectral Imagery Hit paper breakdown → | 2013 | 295 |
| 12 | 2020 | 294 | |
| 13 | Spectral-Spatial Unified Networks for Hyperspectral Image Classification Hit paper breakdown → | 2018 | 291 |
| 14 | Advanced Multi-Sensor Optical Remote Sensing for Urban Land Use and Land Cover Classification: Outcome of the 2018 IEEE GRSS Data Fusion Contest Hit paper breakdown → | 2019 | 281 |
| 15 | Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images Hit paper breakdown → | 2019 | 278 |
| 16 | 2018 | 277 | |
| 17 | Channel Augmented Joint Learning for Visible-Infrared Recognition Hit paper breakdown → | 2021 | 274 |
| 18 | 2015 | 261 | |
| 19 | 2010 | 257 | |
| 20 | 2017 | 257 |
About Bo Du
Bo Du is a scholar working on Media Technology, Computer Vision and Pattern Recognition, Artificial Intelligence, Ocean Engineering and Computational Mathematics, having authored 749 papers that have together received 28.3k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (260 papers), Domain Adaptation and Few-Shot Learning (71 papers), Advanced Neural Network Applications (53 papers), Video Surveillance and Tracking Methods (48 papers), Advanced Graph Neural Networks (29 papers), Medical Image Segmentation Techniques (28 papers), Privacy-Preserving Technologies in Data (24 papers) and Generative Adversarial Networks and Image Synthesis (21 papers). The work is most often cited by research in Media Technology (13.8k citations), Computer Vision and Pattern Recognition (7.4k citations), Computational Mathematics (193 citations), Artificial Intelligence (4.3k citations) and Ocean Engineering (883 citations). Bo Du has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Liangpei Zhang, Lefei Zhang, Dacheng Tao, Chen Wu, Fan Zhang, Mang Ye, Yonghao Xu, Yuxiang Zhang, Zengmao Wang and Yanni Dong. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Image Processing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Transactions on Pattern Analysis and Machine Intelligence and Pattern Recognition.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.