Han Mo Yang
Impact in
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- Generative Adversarial Networks and Image Synthesis
- Advanced Neural Network Applications
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- 3D Shape Modeling and Analysis
Papers in
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- Generative Adversarial Networks and Image Synthesis 5
- Advanced Neural Network Applications 1
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- Infrastructure Maintenance and Monitoring 3
- Co-authors
- Ping Luo (2 shared papers)Wei Liu (2 shared papers)Wangmeng Zuo (1 shared paper)Xiaobao Guo (1 shared paper)Ruimao Zhang (1 shared paper)Yibing Song (1 shared paper)Chongjian Ge (1 shared paper)Yuying Ge (1 shared paper)
- Journals
- Applied Sciences (3 papers)IEEE Access (1 paper)Frontiers in Genetics (1 paper)Case Studies in Thermal Engineering (1 paper)Scientific Reports (1 paper)
- Partner nations
- ChinaSwitzerlandHong Kong
In The Last Decade
Han Mo Yang
13 papers receiving 379 citations
Peers
Comparison fields: 5 of 35
- Computer Vision and Pattern Recognition 330
- Computational Mechanics 41
- Computer Graphics and Computer-Aided Design 8
- Museology 3
- Human-Computer Interaction 4
Countries citing papers authored by Han Mo Yang
This map shows the geographic impact of Han Mo Yang'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 Han Mo Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Han Mo Yang more than expected).
Fields of papers citing papers by Han Mo Yang
This network shows the impact of papers produced by Han Mo Yang. 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 Han Mo Yang. The network helps show where Han Mo Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Han Mo Yang, 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 | 2020 | 225 | |
| 2 | 2021 | 80 | |
| 3 | 2022 | 27 | |
| 4 | 2022 | 15 | |
| 5 | 2020 | 11 | |
| 6 | 2022 | 10 | |
| 7 | 2022 | 8 | |
| 8 | 2023 | 8 | |
| 9 | 2024 | 4 | |
| 10 | 2012 | 2 | |
| 11 | 2021 | 2 | |
| 12 | 2023 | 2 | |
| 13 | 2025 | 1 | |
| 14 | 2025 | 1 | |
| 15 | 2024 | 0 |
About Han Mo Yang
Han Mo Yang is a scholar working on Computer Vision and Pattern Recognition, Civil and Structural Engineering, Architecture, Oceanography and Ocean Engineering, having authored 15 papers that have together received 396 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (5 papers), Infrastructure Maintenance and Monitoring (3 papers), Advanced Neural Network Applications (1 paper), Thermochemical Biomass Conversion Processes (1 paper), Bacteriophages and microbial interactions (1 paper), Underwater Acoustics Research (1 paper), Powder Metallurgy Techniques and Materials (1 paper) and Genomics and Phylogenetic Studies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (330 citations), Computational Mechanics (41 citations), Computer Graphics and Computer-Aided Design (8 citations), Museology (3 citations) and Human-Computer Interaction (4 citations). Han Mo Yang has collaborated with scholars based in China, Switzerland and Hong Kong. Frequent co-authors include Ping Luo, Wei Liu, Wangmeng Zuo, Xiaobao Guo, Ruimao Zhang, Yibing Song, Chongjian Ge, Yuying Ge, Ziwei Liu and Xinrui Yu. Their work appears in journals such as Applied Sciences, IEEE Access, Frontiers in Genetics, Case Studies in Thermal Engineering and Scientific Reports.
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.