Manfred Georg
Impact in
- Human-Computer Interaction top 10%
- Hand Gesture Recognition Systems
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- Human Pose and Action Recognition
- Medical Image Segmentation Techniques
- Face and Expression Recognition
Papers in
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- Digital Media Forensic Detection 2
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- Network Traffic and Congestion Control 3
- Co-authors
- Omid Madani (2 shared papers)David A. Ross (2 shared papers)Robert Pless (3 shared papers)Richard Souvenir (2 shared papers)Andrew Hope (2 shared papers)Hadon Nash (2 shared papers)Esha Uboweja (3 shared papers)Ming Yong (2 shared papers)
- Journals
- Machine Learning (1 paper)Open Scholarship Institutional Repository (Washington University in St. Louis) (1 paper)Asian Conference on Machine Learning (1 paper)
- Partner nations
- United StatesCanada
In The Last Decade
Manfred Georg
10 papers receiving 205 citations
Peers
Comparison fields: 5 of 78
- Human-Computer Interaction 43
- Computer Vision and Pattern Recognition 94
- Computational Mathematics 2
- Radiology, Nuclear Medicine and Imaging 37
- Developmental and Educational Psychology 19
Countries citing papers authored by Manfred Georg
This map shows the geographic impact of Manfred Georg'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 Manfred Georg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manfred Georg more than expected).
Fields of papers citing papers by Manfred Georg
This network shows the impact of papers produced by Manfred Georg. 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 Manfred Georg. The network helps show where Manfred Georg may publish in the future.
Co-authors
The 14 scholars most cited alongside Manfred Georg, 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 | MediaPipe: A Framework for Perceiving and Processing Reality | 2019 | 108 |
| 2 | 2013 | 37 | |
| 3 | 2008 | 27 | |
| 4 | 2010 | 13 | |
| 5 | 2008 | 9 | |
| 6 | 2007 | 6 | |
| 7 | On Using Nearly-Independent Feature Families for High Precision and Confidence | 2012 | 3 |
| 8 | MediaPipe: A Framework for Perceiving and Augmenting Reality | 2019 | 3 |
| 9 | 2005 | 2 | |
| 10 | 2009 | 2 | |
| 11 | A Survey of TCP Optimizations for Wireless Channels | 2006 | 2 |
| 12 | 2025 | 0 | |
| 13 | 2023 | 0 |
About Manfred Georg
Manfred Georg is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Electrical and Electronic Engineering, having authored 13 papers that have together received 212 indexed citations. Recurring topics across this work include Network Traffic and Congestion Control (3 papers), Medical Imaging Techniques and Applications (2 papers), Machine Learning and Data Classification (2 papers), Anomaly Detection Techniques and Applications (2 papers), Digital Media Forensic Detection (2 papers), IPv6, Mobility, Handover, Networks, Security (1 paper), Hearing Impairment and Communication (1 paper) and Advanced Wireless Network Optimization (1 paper). The work is most often cited by research in Human-Computer Interaction (43 citations), Computer Vision and Pattern Recognition (94 citations), Computational Mathematics (2 citations), Radiology, Nuclear Medicine and Imaging (37 citations) and Developmental and Educational Psychology (19 citations). Manfred Georg has collaborated with scholars based in United States and Canada. Frequent co-authors include Omid Madani, David A. Ross, Robert Pless, Richard Souvenir, Andrew Hope, Hadon Nash, Esha Uboweja, Ming Yong, Chuo-Ling Chang and Camillo Lugaresi. Their work appears in journals such as Machine Learning, Open Scholarship Institutional Repository (Washington University in St. Louis) and Asian Conference on Machine Learning.
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.