Yi Lu Murphey
- Automotive Engineering top 0.5%
- Autonomous Vehicle Technology and Safety 31
- Electric and Hybrid Vehicle Technologies 21
- Advanced Battery Technologies Research 16
- Transportation top 5%
- Building and Construction top 2%
- Traffic Prediction and Management Techniques 21
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- Video Surveillance and Tracking Methods 18
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- Electric Vehicles and Infrastructure 17
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- Neural Networks and Applications 17
- Anomaly Detection Techniques and Applications 16
- Journals
- IEEE Transactions on Vehicular Technology (8 papers)SAE technical papers on CD-ROM/SAE technical paper series (6 papers)Pattern Recognition (4 papers)
- Partner nations
- United StatesChinaFrance
In The Last Decade
Yi Lu Murphey
147 papers receiving 2.9k citations
Peers
Comparison fields: 5 of 123
- Automotive Engineering 1.4k
- Control and Systems Engineering 745
- Safety, Risk, Reliability and Quality 220
- Transportation 148
- Building and Construction 296
Countries citing papers authored by Yi Lu Murphey
This map shows the geographic impact of Yi Lu Murphey'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 Lu Murphey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yi Lu Murphey more than expected).
Fields of papers citing papers by Yi Lu Murphey
This network shows the impact of papers produced by Yi Lu Murphey. 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 Lu Murphey. The network helps show where Yi Lu Murphey may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yi Lu Murphey, 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 | 2026 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 6 | |
| 5 | 2023 | 1 | |
| 6 | 2022 | 8 | |
| 7 | 2022 | 3 | |
| 8 | 2019 | 86 | |
| 9 | 2018 | 65 | |
| 10 | 2018 | 21 | |
| 11 | 2014 | 49 | |
| 12 | 2013 | 2 | |
| 13 | 2012 | 148 | |
| 14 | 2010 | 3 | |
| 15 | 2009 | 2 | |
| 16 | 2008 | 8 | |
| 17 | 2004 | 24 | |
| 18 | Registering Video with Virtual Imagery using Robust Image Features. | 2001 | 0 |
| 19 | Registering Real-Scene to Virtual Imagery Using Robust Image Features | 2001 | 0 |
| 20 | Incremental learning in a fuzzy intelligent system | 1999 | 1 |
About Yi Lu Murphey
Yi Lu Murphey is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 152 papers that have together received 3.0k indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (31 papers), Traffic Prediction and Management Techniques (21 papers), Electric and Hybrid Vehicle Technologies (21 papers), Video Surveillance and Tracking Methods (18 papers), Electric Vehicles and Infrastructure (17 papers), Neural Networks and Applications (17 papers), Advanced Battery Technologies Research (16 papers) and Anomaly Detection Techniques and Applications (16 papers). The work is most often cited by research in Automotive Engineering (1.4k citations), Control and Systems Engineering (745 citations) and Safety, Risk, Reliability and Quality (220 citations). Yi Lu Murphey has collaborated with scholars based in United States, China and France. Frequent co-authors include M. Abul Masrur, Jungme Park, Zhihang Chen, R. S. Milton, Ming Kuang, Hong Guo, Gao Jun, Baifang Zhang, M.L. Kuang and Jacob Crossman. Their work appears in journals such as IEEE Transactions on Vehicular Technology, SAE technical papers on CD-ROM/SAE technical paper series, Pattern Recognition, IEEE Access and Applied Intelligence.
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.