Sze Kim Pang
- Artificial Intelligence top 5%
- Target Tracking and Data Fusion in Sensor Networks 9
- Bayesian Methods and Mixture Models 5
- Gaussian Processes and Bayesian Inference 3
- Neural Networks and Applications 1
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- Video Surveillance and Tracking Methods 4
- Advanced Vision and Imaging 1
- Aerospace Engineering top 10%
- Signal Processing top 10%
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- Advanced Image Fusion Techniques 1
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- Distributed Sensor Networks and Detection Algorithms 1
- Co-authors
- Simon GodsillFrançois SeptierJack LiAvishy CarmiLyudmila MihaylovaAmadou GningSimon MaskellMarcus Y. Chen
- Journals
- IEEE Journal of Selected Topics in Signal Processing (1 paper)IEEE Transactions on Aerospace and Electronic Systems (1 paper)Digital Signal Processing (1 paper)
- Partner nations
- United KingdomSingaporeFrance
In The Last Decade
Sze Kim Pang
14 papers receiving 501 citations
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 358
- Computer Vision and Pattern Recognition 114
- Aerospace Engineering 116
- Signal Processing 50
- Instrumentation 15
Countries citing papers authored by Sze Kim Pang
This map shows the geographic impact of Sze Kim Pang'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 Sze Kim Pang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sze Kim Pang more than expected).
Fields of papers citing papers by Sze Kim Pang
This network shows the impact of papers produced by Sze Kim Pang. 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 Sze Kim Pang. The network helps show where Sze Kim Pang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sze Kim Pang, 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 | 2015 | 11 | |
| 2 | 2013 | 160 | |
| 3 | 2013 | 7 | |
| 4 | Visual tracking with generative template model based on Riemannian manifold of covariances | 2011 | 9 |
| 5 | 2011 | 95 | |
| 6 | 2011 | 56 | |
| 7 | 2011 | 75 | |
| 8 | 2010 | 1 | |
| 9 | 2009 | 37 | |
| 10 | 2009 | 16 | |
| 11 | 2008 | 3 | |
| 12 | 2008 | 34 | |
| 13 | 2007 | 8 | |
| 14 | 2006 | 3 |
About Sze Kim Pang
Sze Kim Pang is a scholar working on Artificial Intelligence, Instrumentation, Computer Vision and Pattern Recognition, Statistics and Probability and Media Technology, having authored 14 papers that have together received 515 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (9 papers), Bayesian Methods and Mixture Models (5 papers), Video Surveillance and Tracking Methods (4 papers), Gaussian Processes and Bayesian Inference (3 papers), Advanced Image Fusion Techniques (1 paper), Neural Networks and Applications (1 paper), Distributed Sensor Networks and Detection Algorithms (1 paper) and Advanced Vision and Imaging (1 paper). The work is most often cited by research in Artificial Intelligence (358 citations), Computer Vision and Pattern Recognition (114 citations), Aerospace Engineering (116 citations), Signal Processing (50 citations) and Instrumentation (15 citations). Sze Kim Pang has collaborated with scholars based in United Kingdom, Singapore and France. Frequent co-authors include Simon Godsill, François Septier, Jack Li, Avishy Carmi, Lyudmila Mihaylova, Amadou Gning, Simon Maskell, Marcus Y. Chen, Richard E. Turner and Yves F. Atchadé. Their work appears in journals such as IEEE Journal of Selected Topics in Signal Processing, IEEE Transactions on Aerospace and Electronic Systems, Digital Signal Processing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and IEEE Transactions on Signal Processing.
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.