Yi Han
Impact in
- Automotive Engineering top 10%
- Autonomous Vehicle Technology and Safety
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- Advanced Neural Network Applications
Papers in
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- Autonomous Vehicle Technology and Safety 6
- Transportation and Mobility Innovations 4
- Vehicle Dynamics and Control Systems 3
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- Advanced Neural Network Applications 5
- Co-authors
- Sung‐Sau So (1 shared paper)Guangfeng Yang (1 shared paper)Wei Wei (1 shared paper)Joon Huang Chuah (1 shared paper)Ming Liu (3 shared papers)Mengjiao Cai (1 shared paper)Lujia Wang (2 shared papers)Weishan Zhang (2 shared papers)
In The Last Decade
Yi Han
28 papers receiving 730 citations
Yi Han's Hit Papers
Peers
Comparison fields: 5 of 145
- Automotive Engineering 83
- Computer Vision and Pattern Recognition 107
- Building and Construction 63
- Industrial and Manufacturing Engineering 37
- Artificial Intelligence 113
Countries citing papers authored by Yi Han
This map shows the geographic impact of Yi Han'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 Yi Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yi Han more than expected).
Fields of papers citing papers by Yi Han
This network shows the impact of papers produced by Yi Han. 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 Yi Han. The network helps show where Yi Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Yi Han, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Overview of Artificial Neural Networks Hit paper breakdown → | 2008 | 445 |
| 2 | 2022 | 64 | |
| 3 | 2022 | 40 | |
| 4 | 2021 | 40 | |
| 5 | 2023 | 26 | |
| 6 | 2020 | 25 | |
| 7 | 2018 | 25 | |
| 8 | 2022 | 17 | |
| 9 | 2022 | 7 | |
| 10 | 2018 | 7 | |
| 11 | 2019 | 5 | |
| 12 | 2022 | 5 | |
| 13 | 2024 | 5 | |
| 14 | 2025 | 4 | |
| 15 | 2020 | 4 | |
| 16 | 2024 | 4 | |
| 17 | 2023 | 4 | |
| 18 | 2023 | 4 | |
| 19 | 2024 | 3 | |
| 20 | 2023 | 3 |
About Yi Han
Yi Han is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition, Building and Construction, Industrial and Manufacturing Engineering and Control and Systems Engineering, having authored 32 papers that have together received 750 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (6 papers), Advanced Neural Network Applications (5 papers), Transportation and Mobility Innovations (4 papers), Traffic control and management (4 papers), Vehicle Dynamics and Control Systems (3 papers), Vehicle Routing Optimization Methods (3 papers), Traffic Prediction and Management Techniques (3 papers) and Traffic and Road Safety (3 papers). The work is most often cited by research in Automotive Engineering (83 citations), Computer Vision and Pattern Recognition (107 citations), Building and Construction (63 citations), Industrial and Manufacturing Engineering (37 citations) and Artificial Intelligence (113 citations). Yi Han has collaborated with scholars based in China, Hong Kong and Finland. Frequent co-authors include Sung‐Sau So, Guangfeng Yang, Wei Wei, Joon Huang Chuah, Ming Liu, Mengjiao Cai, Lujia Wang, Weishan Zhang, Ting Xu and Long Qi. Their work appears in journals such as IEEE Access, Journal of Traffic and Transportation Engineering (English Edition), Applied Sciences, IEEE Transactions on Intelligent Transportation Systems and IEEE Transactions on Industrial Informatics.
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.