Lan Wu
Impact in
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety
-
- Face recognition and analysis
- Image Enhancement Techniques
- Face and Expression Recognition
Papers in
-
- Gas Sensing Nanomaterials and Sensors 6
- Semiconductor Lasers and Optical Devices 5
- Photonic and Optical Devices 5
- Silicon and Solar Cell Technologies 5
- Co-authors
- Kunpeng Zhang (6 shared papers)Zhengbing He (3 shared papers)Liang Zhao (2 shared papers)Xiaoliang Feng (3 shared papers)Liang Zheng (1 shared paper)Haofeng Hu (3 shared papers)Tiegen Liu (3 shared papers)Xiaobo Li (2 shared papers)
- Journals
- Applied Optics (6 papers)Remote Sensing of Environment (4 papers)Journal of Applied Physics (3 papers)Optics Express (2 papers)IEEE Access (2 papers)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Lan Wu
80 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 127
- Automotive Engineering 184
- Computer Vision and Pattern Recognition 316
- Building and Construction 176
- Signal Processing 115
- Transportation 63
Countries citing papers authored by Lan Wu
This map shows the geographic impact of Lan Wu'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 Lan Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lan Wu more than expected).
Fields of papers citing papers by Lan Wu
This network shows the impact of papers produced by Lan Wu. 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 Lan Wu. The network helps show where Lan Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Lan Wu, 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 94 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 132 | |
| 2 | 2018 | 120 | |
| 3 | 2022 | 107 | |
| 4 | 2022 | 96 | |
| 5 | 2022 | 83 | |
| 6 | 2021 | 72 | |
| 7 | 2023 | 68 | |
| 8 | 2020 | 50 | |
| 9 | 2020 | 30 | |
| 10 | 2017 | 24 | |
| 11 | 2018 | 23 | |
| 12 | 2022 | 23 | |
| 13 | 2010 | 14 | |
| 14 | 2006 | 12 | |
| 15 | 2017 | 12 | |
| 16 | 2024 | 11 | |
| 17 | 2019 | 11 | |
| 18 | 2018 | 10 | |
| 19 | 2024 | 9 | |
| 20 | 2011 | 8 |
About Lan Wu
Lan Wu is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering, Biomedical Engineering and Materials Chemistry, having authored 94 papers that have together received 1.1k indexed citations. Recurring topics across this work include Fault Detection and Control Systems (6 papers), Traffic Prediction and Management Techniques (6 papers), Atmospheric and Environmental Gas Dynamics (6 papers), Gas Sensing Nanomaterials and Sensors (6 papers), Semiconductor Lasers and Optical Devices (5 papers), Photonic and Optical Devices (5 papers), Silicon and Solar Cell Technologies (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). The work is most often cited by research in Automotive Engineering (184 citations), Computer Vision and Pattern Recognition (316 citations), Building and Construction (176 citations), Signal Processing (115 citations) and Transportation (63 citations). Lan Wu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Kunpeng Zhang, Zhengbing He, Liang Zhao, Xiaoliang Feng, Liang Zheng, Haofeng Hu, Tiegen Liu, Xiaobo Li, Hui Wang and Lin Zhao. Their work appears in journals such as Applied Optics, Remote Sensing of Environment, Journal of Applied Physics, Optics Express and IEEE Access.
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.