Xiaodan Deng
Impact in
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- Pulsars and Gravitational Waves Research
- Radio Astronomy Observations and Technology
- Gamma-ray bursts and supernovae
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- Machine Learning and ELM
- Domain Adaptation and Few-Shot Learning
- AI in cancer detection
- Seismology and Earthquake Studies
Papers in
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- Generative Adversarial Networks and Image Synthesis 2
- Face and Expression Recognition 2
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- Machine Learning and ELM 3
- Neural Networks and Applications 2
- Co-authors
- Ping Guo (7 shared papers)Qian Yin (8 shared papers)Zhichen Pan (1 shared paper)Xuhong Yu (1 shared paper)Weiwei Zhu (1 shared paper)Zhijie Liu (1 shared paper)Xiaoyao Xie (1 shared paper)Chenchen Miao (1 shared paper)
In The Last Decade
Xiaodan Deng
13 papers receiving 90 citations
Peers
Comparison fields: 5 of 42
- Astronomy and Astrophysics 28
- Artificial Intelligence 37
- Computer Vision and Pattern Recognition 17
- Oncology 14
- Computational Mechanics 11
Countries citing papers authored by Xiaodan Deng
This map shows the geographic impact of Xiaodan Deng'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 Xiaodan Deng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaodan Deng more than expected).
Fields of papers citing papers by Xiaodan Deng
This network shows the impact of papers produced by Xiaodan Deng. 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 Xiaodan Deng. The network helps show where Xiaodan Deng may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaodan Deng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 27 | |
| 2 | 2019 | 12 | |
| 3 | 2024 | 11 | |
| 4 | 2021 | 10 | |
| 5 | 2021 | 10 | |
| 6 | 2021 | 6 | |
| 7 | 2018 | 4 | |
| 8 | 2023 | 3 | |
| 9 | 2019 | 3 | |
| 10 | 2019 | 2 | |
| 11 | 2022 | 2 | |
| 12 | 2024 | 1 | |
| 13 | 2019 | 1 | |
| 14 | 2023 | 0 | |
| 15 | 2022 | 0 |
About Xiaodan Deng
Xiaodan Deng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Astronomy and Astrophysics and Oncology, having authored 15 papers that have together received 92 indexed citations. Recurring topics across this work include Machine Learning and ELM (3 papers), Forensic Anthropology and Bioarchaeology Studies (2 papers), Cutaneous Melanoma Detection and Management (2 papers), Radio Astronomy Observations and Technology (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Face and Expression Recognition (2 papers), 3D Shape Modeling and Analysis (2 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Astronomy and Astrophysics (28 citations), Artificial Intelligence (37 citations), Computer Vision and Pattern Recognition (17 citations), Oncology (14 citations) and Computational Mechanics (11 citations). Xiaodan Deng has collaborated with scholars based in China, Germany and Malaysia. Frequent co-authors include Ping Guo, Qian Yin, Zhichen Pan, Xuhong Yu, Weiwei Zhu, Zhijie Liu, Xiaoyao Xie, Chenchen Miao, Pei Wang and Xin Zheng. Their work appears in journals such as Computers & Graphics, Neurocomputing, Monthly Notices of the Royal Astronomical Society, Neural Computing and Applications and Acta Neurobiologiae Experimentalis.
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.