Alexander Gepperth
Impact in
- Human-Computer Interaction top 5%
- Hand Gesture Recognition Systems
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- Video Surveillance and Tracking Methods
- Human Pose and Action Recognition
- Multimodal Machine Learning Applications
Papers in
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- Neural Networks and Applications 15
- Domain Adaptation and Few-Shot Learning 13
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- Advanced Neural Network Applications 11
- Video Surveillance and Tracking Methods 10
- Human Pose and Action Recognition 8
- Visual Attention and Saliency Detection 6
- Co-authors
- M. Ortíz (5 shared papers)Jannik Fritsch (11 shared papers)Franz Kümmert (2 shared papers)Stefan Roth (3 shared papers)Uwe Handmann (6 shared papers)Johann Edelbrunner (1 shared paper)David Filliat (3 shared papers)Christian Goerick (8 shared papers)
In The Last Decade
Alexander Gepperth
66 papers receiving 598 citations
Peers
Comparison fields: 5 of 75
- Human-Computer Interaction 83
- Computer Vision and Pattern Recognition 279
- Artificial Intelligence 299
- Automotive Engineering 95
- Computer Networks and Communications 81
Countries citing papers authored by Alexander Gepperth
This map shows the geographic impact of Alexander Gepperth'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 Alexander Gepperth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Gepperth more than expected).
Fields of papers citing papers by Alexander Gepperth
This network shows the impact of papers produced by Alexander Gepperth. 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 Alexander Gepperth. The network helps show where Alexander Gepperth may publish in the future.
Co-authors
The 25 scholars most cited alongside Alexander Gepperth, 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 73 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 101 | |
| 2 | 2020 | 48 | |
| 3 | 2011 | 41 | |
| 4 | 2019 | 37 | |
| 5 | 2008 | 23 | |
| 6 | 2005 | 23 | |
| 7 | 2017 | 19 | |
| 8 | 2019 | 18 | |
| 9 | 2019 | 18 | |
| 10 | 2017 | 16 | |
| 11 | 2006 | 15 | |
| 12 | 2019 | 14 | |
| 13 | 2011 | 14 | |
| 14 | 2006 | 13 | |
| 15 | 2019 | 12 | |
| 16 | 2018 | 12 | |
| 17 | 2008 | 11 | |
| 18 | 2016 | 11 | |
| 19 | 2021 | 11 | |
| 20 | 2013 | 11 |
About Alexander Gepperth
Alexander Gepperth is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Human-Computer Interaction and Aerospace Engineering, having authored 73 papers that have together received 618 indexed citations. Recurring topics across this work include Neural Networks and Applications (15 papers), Domain Adaptation and Few-Shot Learning (13 papers), Advanced Neural Network Applications (11 papers), Hand Gesture Recognition Systems (11 papers), Video Surveillance and Tracking Methods (10 papers), Human Pose and Action Recognition (8 papers), Visual Attention and Saliency Detection (6 papers) and Neural dynamics and brain function (6 papers). The work is most often cited by research in Human-Computer Interaction (83 citations), Computer Vision and Pattern Recognition (279 citations), Artificial Intelligence (299 citations), Automotive Engineering (95 citations) and Computer Networks and Communications (81 citations). Alexander Gepperth has collaborated with scholars based in Germany, France and Japan. Frequent co-authors include M. Ortíz, Jannik Fritsch, Franz Kümmert, Stefan Roth, Uwe Handmann, Johann Edelbrunner, David Filliat, Christian Goerick, Christian Igel and Marcus Kleinehagenbrock. Their work appears in journals such as Cognitive Computation, Lecture notes in computer science, Neural Processing Letters, Neurocomputing and IEEE Transactions on Network and Service Management.
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.