Peter Pinggera
Impact in
- Automotive Engineering top 2%
- Autonomous Vehicle Technology and Safety
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- Advanced Neural Network Applications
- Advanced Vision and Imaging
Papers in
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- Advanced Vision and Imaging 7
- Advanced Neural Network Applications 3
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- Autonomous Vehicle Technology and Safety 3
- Co-authors
- Uwe Franke (6 shared papers)Carsten Rother (2 shared papers)Stefan K. Gehrig (2 shared papers)Sebastian Ramos (2 shared papers)Rudolf Mester (4 shared papers)Horst Bischof (1 shared paper)Toby P. Breckon (1 shared paper)Björn Ommer (2 shared papers)
- Journals
- Lecture notes in computer science (5 papers)IEEE Intelligent Transportation Systems Conference (ITSC) (1 paper)Proceedings - IEEE International Conference on Robotics and Automation/Proceedings (1 paper)IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)IEEE Intelligent Vehicles Symposium (1 paper)
In The Last Decade
Peter Pinggera
12 papers receiving 558 citations
Peers
Comparison fields: 5 of 45
- Automotive Engineering 189
- Computer Vision and Pattern Recognition 381
- Instrumentation 15
- Artificial Intelligence 102
- Aerospace Engineering 73
Countries citing papers authored by Peter Pinggera
This map shows the geographic impact of Peter Pinggera'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 Peter Pinggera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Pinggera more than expected).
Fields of papers citing papers by Peter Pinggera
This network shows the impact of papers produced by Peter Pinggera. 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 Peter Pinggera. The network helps show where Peter Pinggera may publish in the future.
Co-authors
The 17 scholars most cited alongside Peter Pinggera, 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 | 2016 | 143 | |
| 2 | 2017 | 133 | |
| 3 | 2016 | 60 | |
| 4 | 2021 | 60 | |
| 5 | 2019 | 52 | |
| 6 | 2012 | 51 | |
| 7 | 2014 | 34 | |
| 8 | 2015 | 24 | |
| 9 | 2019 | 7 | |
| 10 | 2019 | 5 | |
| 11 | 2013 | 3 | |
| 12 | 2021 | 3 |
About Peter Pinggera
Peter Pinggera is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering, Aerospace Engineering, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 12 papers that have together received 575 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (7 papers), Autonomous Vehicle Technology and Safety (3 papers), Advanced Neural Network Applications (3 papers) and Robotics and Sensor-Based Localization (1 paper). The work is most often cited by research in Automotive Engineering (189 citations), Computer Vision and Pattern Recognition (381 citations), Instrumentation (15 citations), Artificial Intelligence (102 citations) and Aerospace Engineering (73 citations). Peter Pinggera has collaborated with scholars based in Germany, Sweden and Austria. Frequent co-authors include Uwe Franke, Carsten Rother, Stefan K. Gehrig, Sebastian Ramos, Rudolf Mester, Horst Bischof, Toby P. Breckon, Björn Ommer, Christoph Stiller and Marc Pollefeys. Their work appears in journals such as Lecture notes in computer science, IEEE Intelligent Transportation Systems Conference (ITSC), Proceedings - IEEE International Conference on Robotics and Automation/Proceedings, IEEE/CVF International Conference on Computer Vision (ICCV) and IEEE Intelligent Vehicles Symposium.
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.