Johannes Stallkamp
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 1%
- Media Technology top 0.5%
- Civil and Structural Engineering top 5%
- Electrical and Electronic Engineering
- Co-authors
- Marc SchlipsingJan SalmenChristian IgelSebastian HoubenHazım Kemal EkenelRainer StiefelhagenMichael MatthiasHua Gao
- Topics
- Face and Expression Recognition (4 papers)Face recognition and analysis (4 papers)Video Surveillance and Tracking Methods (4 papers)
In The Last Decade
Johannes Stallkamp
10 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 90
- Computer Vision and Pattern Recognition 1.6k
- Artificial Intelligence 846
- Media Technology 633
- Civil and Structural Engineering 285
- Electrical and Electronic Engineering 196
Countries citing papers authored by Johannes Stallkamp
This map shows the geographic impact of Johannes Stallkamp'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 Johannes Stallkamp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johannes Stallkamp more than expected).
Fields of papers citing papers by Johannes Stallkamp
This network shows the impact of papers produced by Johannes Stallkamp. 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 Johannes Stallkamp. The network helps show where Johannes Stallkamp may publish in the future.
Co-authorship network of co-authors of Johannes Stallkamp
This figure shows the co-authorship network connecting the top 25 collaborators of Johannes Stallkamp. A scholar is included among the top collaborators of Johannes Stallkamp based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Johannes Stallkamp. Johannes Stallkamp is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 58 | |
| 2 | Detection of traffic signs in real-world images: The German traffic sign detection benchmarkbreakdown → | 594 |
| 3 | Proposal for IJCNN 2013 competition: The German Traffic Sign Detection Benchmark | 1 |
| 4 | Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognitionbreakdown → | 886 |
| 5 | 5 | |
| 6 | The German Traffic Sign Recognition Benchmark: A multi-class classification competitionbreakdown → | 648 |
| 7 | 20 | |
| 8 | 70 | |
| 9 | 24 | |
| 10 | Video-based driver identification using local appearance face recognition | 5 |
About Johannes Stallkamp
Johannes Stallkamp is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Human-Computer Interaction, having authored 10 papers that have together received 2.3k indexed citations. Recurring topics across this work include Face and Expression Recognition (4 papers), Face recognition and analysis (4 papers) and Video Surveillance and Tracking Methods (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.6k citations), Media Technology (633 citations) and Human-Computer Interaction (172 citations). Johannes Stallkamp has collaborated with scholars based in Germany, Denmark and Türkiye. Frequent co-authors include Marc Schlipsing, Jan Salmen, Christian Igel, Sebastian Houben, Hazım Kemal Ekenel, Rainer Stiefelhagen, Michael Matthias, Hua Gao, Hakan Erdoğan and Aytül Erçi̇l. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, Neural Networks and Computer Vision and Image Understanding.
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.