Xiaodan Hu
Impact in
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- Advanced Image Processing Techniques
- Image and Signal Denoising Methods
- Advanced Vision and Imaging
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- Animal Behavior and Welfare Studies
Papers in
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- Advanced Vision and Imaging 4
- Advanced Image Processing Techniques 4
- Image and Signal Denoising Methods 2
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- Animal Behavior and Welfare Studies 2
- Co-authors
- Mohamed A. Naiel (3 shared papers)Paul Fieguth (3 shared papers)Alexander Wong (1 shared paper)Brian Aldridge (1 shared paper)Narendra Ahuja (2 shared papers)Angela R Green-Miller (2 shared papers)Isabella Condotta (2 shared papers)John M. Hart (1 shared paper)
- Journals
- Computers and Electronics in Agriculture (2 papers)Signal Processing Image Communication (1 paper)Textile Research Journal (1 paper)Remote Sensing (1 paper)Journal of Integrative Agriculture (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Xiaodan Hu
8 papers receiving 112 citations
Peers
Comparison fields: 5 of 44
- Computer Vision and Pattern Recognition 55
- Small Animals 18
- Media Technology 17
- Computational Mathematics 1
- Food Science 15
Countries citing papers authored by Xiaodan Hu
This map shows the geographic impact of Xiaodan Hu'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 Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaodan Hu more than expected).
Fields of papers citing papers by Xiaodan Hu
This network shows the impact of papers produced by Xiaodan Hu. 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 Hu. The network helps show where Xiaodan Hu may publish in the future.
Co-authors
The 23 scholars most cited alongside Xiaodan Hu, 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 | 72 | |
| 2 | 2022 | 26 | |
| 3 | 2024 | 6 | |
| 4 | 2024 | 5 | |
| 5 | 2023 | 2 | |
| 6 | Analysis on the factors influencing the accuracy of human photogrammetry | 2006 | 1 |
| 7 | 2019 | 1 | |
| 8 | 2021 | 1 | |
| 9 | 2025 | 0 |
About Xiaodan Hu
Xiaodan Hu is a scholar working on Computer Vision and Pattern Recognition, Small Animals, Aerospace Engineering, Food Science and Electrical and Electronic Engineering, having authored 9 papers that have together received 114 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (4 papers), Advanced Image Processing Techniques (4 papers), Image and Signal Denoising Methods (2 papers), Animal Behavior and Welfare Studies (2 papers), Advanced Measurement and Detection Methods (2 papers), Food Supply Chain Traceability (2 papers), Smart Agriculture and AI (2 papers) and Meat and Animal Product Quality (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (55 citations), Small Animals (18 citations), Media Technology (17 citations), Computational Mathematics (1 citation) and Food Science (15 citations). Xiaodan Hu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Mohamed A. Naiel, Paul Fieguth, Alexander Wong, Brian Aldridge, Narendra Ahuja, Angela R Green-Miller, Isabella Condotta, John M. Hart, Ryan N. Dilger and Yiqi Wu. Their work appears in journals such as Computers and Electronics in Agriculture, Signal Processing Image Communication, Textile Research Journal, Remote Sensing and Journal of Integrative Agriculture.
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.