Peter Pinggera
Impact in
-
- Advanced Neural Network Applications
- Advanced Vision and Imaging
- Video Surveillance and Tracking Methods
- Advanced Image and Video Retrieval Techniques
- Image Enhancement Techniques
- Advanced Image Processing Techniques
- Automotive Engineering top 10%
- Autonomous Vehicle Technology and Safety
Papers in ⓘ
-
- Advanced Vision and Imaging 3
- Video Surveillance and Tracking Methods 2
- Advanced Neural Network Applications 2
- Human Pose and Action Recognition 1
- Image Enhancement Techniques 1
-
- Autonomous Vehicle Technology and Safety 3
- Co-authors
- Uwe Franke (2 shared papers)Stefan Gehrig (1 shared paper)Sebastian Ramos (1 shared paper)Carsten Rother (1 shared paper)Toby P. Breckon (1 shared paper)Horst Bischof (1 shared paper)Björn Ommer (2 shared papers)Frank Moosmann (1 shared paper)
- Journals
- Durham Research Online (Durham University) (1 paper)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)
- Partner nations
- GermanySwedenUnited Kingdom
In The Last Decade
Peter Pinggera
5 papers receiving 230 citations
Peers
Comparison fields: 5 of 48
- Computer Vision and Pattern Recognition 171
- Automotive Engineering 62
- Media Technology 24
- Computer Graphics and Computer-Aided Design 8
- Aerospace Engineering 52
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 10 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 | 2017 | 115 | |
| 2 | 2021 | 55 | |
| 3 | 2012 | 44 | |
| 4 | 2015 | 19 | |
| 5 | 2021 | 3 |
About Peter Pinggera
Peter Pinggera is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering, Aerospace Engineering, Infectious Diseases and Organic Chemistry, having authored 5 papers that have together received 236 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (3 papers), Autonomous Vehicle Technology and Safety (3 papers), Video Surveillance and Tracking Methods (2 papers), Robotics and Sensor-Based Localization (2 papers), Advanced Neural Network Applications (2 papers), Human Pose and Action Recognition (1 paper), Image Enhancement Techniques (1 paper) and Infrared Target Detection Methodologies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (171 citations), Automotive Engineering (62 citations), Media Technology (24 citations), Computer Graphics and Computer-Aided Design (8 citations) and Aerospace Engineering (52 citations). Peter Pinggera has collaborated with scholars based in Germany, Sweden and United Kingdom. Frequent co-authors include Uwe Franke, Stefan Gehrig, Sebastian Ramos, Carsten Rother, Toby P. Breckon, Horst Bischof, Björn Ommer, Frank Moosmann, Andreas Geiger and Rudolf Mester. Their work appears in journals such as Durham Research Online (Durham University) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.