Jonas Uhrig
Impact in
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- Video Surveillance and Tracking Methods
- Advanced Neural Network Applications
- Human Pose and Action Recognition
- Advanced Image and Video Retrieval Techniques
- Advanced Vision and Imaging
Papers in
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- Advanced Image and Video Retrieval Techniques 3
- Advanced Neural Network Applications 3
- Advanced Vision and Imaging 2
- Visual Attention and Saliency Detection 1
- Medical Image Segmentation Techniques 1
- Image and Object Detection Techniques 1
- Co-authors
- Thomas Brox (3 shared papers)Uwe Franke (2 shared papers)Eike Rehder (1 shared paper)Bernt Schiele (1 shared paper)Alexander Kirillov (1 shared paper)Carsten Rother (1 shared paper)Bjoern Andres (1 shared paper)Evgeny Levinkov (1 shared paper)
- Journals
- Max Planck Digital Library (1 paper)FreiDok plus (Universitätsbibliothek Freiburg) (1 paper)ArXiv.org (1 paper)
- Partner nations
- GermanyUnited States
In The Last Decade
Jonas Uhrig
5 papers receiving 108 citations
Peers
Comparison fields: 5 of 34
- Computer Vision and Pattern Recognition 98
- Structural Biology 2
- Artificial Intelligence 38
- Automotive Engineering 11
- Safety, Risk, Reliability and Quality 6
Countries citing papers authored by Jonas Uhrig
This map shows the geographic impact of Jonas Uhrig'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 Jonas Uhrig with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonas Uhrig more than expected).
Fields of papers citing papers by Jonas Uhrig
This network shows the impact of papers produced by Jonas Uhrig. 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 Jonas Uhrig. The network helps show where Jonas Uhrig may publish in the future.
Co-authors
The 15 scholars most cited alongside Jonas Uhrig, 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 | 58 | |
| 2 | 2018 | 44 | |
| 3 | Pixel-level encoding and depth layering for instance-level semantic segmentation | 2016 | 5 |
| 4 | 2023 | 3 | |
| 5 | 2025 | 1 |
About Jonas Uhrig
Jonas Uhrig is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Computer Graphics and Computer-Aided Design and Industrial and Manufacturing Engineering, having authored 5 papers that have together received 111 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (3 papers), Advanced Neural Network Applications (3 papers), Advanced Vision and Imaging (2 papers), Visual Attention and Saliency Detection (1 paper), Medical Image Segmentation Techniques (1 paper), Computer Graphics and Visualization Techniques (1 paper), Industrial Vision Systems and Defect Detection (1 paper) and Image and Object Detection Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (98 citations), Structural Biology (2 citations), Artificial Intelligence (38 citations), Automotive Engineering (11 citations) and Safety, Risk, Reliability and Quality (6 citations). Jonas Uhrig has collaborated with scholars based in Germany and United States. Frequent co-authors include Thomas Brox, Uwe Franke, Eike Rehder, Bernt Schiele, Alexander Kirillov, Carsten Rother, Bjoern Andres, Evgeny Levinkov, Siyu Tang and Eldar Insafutdinov. Their work appears in journals such as Max Planck Digital Library, FreiDok plus (Universitätsbibliothek Freiburg) and ArXiv.org.
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.