M. Lu
Impact in
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- Video Surveillance and Tracking Methods
- Advanced Image and Video Retrieval Techniques
- Advanced Vision and Imaging
- Human Pose and Action Recognition
- Image Enhancement Techniques
- Video Analysis and Summarization
- Advanced Steganography and Watermarking Techniques
- Signal Processing top 10%
Papers in ⓘ
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- Video Surveillance and Tracking Methods 6
- Advanced Vision and Imaging 2
- Face recognition and analysis 1
- Optical measurement and interference techniques 1
- Human Pose and Action Recognition 1
- Image Enhancement Techniques 1
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- Energy Efficient Wireless Sensor Networks 1
- Co-authors
- Arun Hampapur (6 shared papers)Yingli Tian (4 shared papers)Jonathan H. Connell (4 shared papers)Lisa M. Brown (4 shared papers)Sharath Pankanti (2 shared papers)Ahmet Ekin (2 shared papers)Andrew Senior (3 shared papers)Norman Haas (1 shared paper)
- Partner nations
- United StatesNetherlandsChina
In The Last Decade
M. Lu
6 papers receiving 597 citations
Peers
Comparison fields: 5 of 59
- Computer Vision and Pattern Recognition 547
- Signal Processing 57
- Safety, Risk, Reliability and Quality 44
- Media Technology 35
- Artificial Intelligence 123
Countries citing papers authored by M. Lu
This map shows the geographic impact of M. Lu'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 M. Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Lu more than expected).
Fields of papers citing papers by M. Lu
This network shows the impact of papers produced by M. Lu. 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 M. Lu. The network helps show where M. Lu may publish in the future.
Co-authors
The 9 scholars most cited alongside M. Lu, 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 | 2005 | 207 | |
| 2 | 2005 | 173 | |
| 3 | 2005 | 145 | |
| 4 | 2006 | 62 | |
| 5 | 2005 | 44 | |
| 6 | 2007 | 9 |
About M. Lu
M. Lu is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Aerospace Engineering, Artificial Intelligence and Electrical and Electronic Engineering, having authored 6 papers that have together received 640 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (6 papers), Advanced Vision and Imaging (2 papers), Energy Efficient Wireless Sensor Networks (1 paper), IoT-based Smart Home Systems (1 paper), Face recognition and analysis (1 paper), Optical measurement and interference techniques (1 paper), Human Pose and Action Recognition (1 paper) and Image Enhancement Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (547 citations), Signal Processing (57 citations), Safety, Risk, Reliability and Quality (44 citations), Media Technology (35 citations) and Artificial Intelligence (123 citations). M. Lu has collaborated with scholars based in United States, Netherlands and China. Frequent co-authors include Arun Hampapur, Yingli Tian, Jonathan H. Connell, Lisa M. Brown, Sharath Pankanti, Ahmet Ekin, Andrew Senior, Norman Haas and Chiao-Fe Shu. Their work appears in journals such as IEEE Security & Privacy and IEEE Signal Processing Magazine.
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.