Johan Vertens
Impact in
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- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Advanced Vision and Imaging
- Robotic Path Planning Algorithms
- Geology top 10%
- 3D Surveying and Cultural Heritage
Papers in
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- Advanced Neural Network Applications 4
- Advanced Image and Video Retrieval Techniques 2
- Advanced Vision and Imaging 2
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- Autonomous Vehicle Technology and Safety 3
- Vehicle Dynamics and Control Systems 1
- Co-authors
- Wolfram Burgard (8 shared papers)Abhinav Valada (3 shared papers)Lukas Luft (2 shared papers)Alexander Schaefer (2 shared papers)Daniel Buscher (1 shared paper)Fabian Fischer (1 shared paper)Albert Gollhofer (1 shared paper)Rui Zhang (1 shared paper)
- Journals
- Robotics and Autonomous Systems (1 paper)2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)Springer proceedings in advanced robotics (1 paper)IEEE Conference Proceedings (1 paper)arXiv (Cornell University) (2 papers)
In The Last Decade
Johan Vertens
10 papers receiving 301 citations
Peers
Comparison fields: 5 of 51
- Computer Vision and Pattern Recognition 207
- Geology 39
- Aerospace Engineering 124
- Environmental Engineering 64
- Automotive Engineering 46
Countries citing papers authored by Johan Vertens
This map shows the geographic impact of Johan Vertens'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 Johan Vertens with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johan Vertens more than expected).
Fields of papers citing papers by Johan Vertens
This network shows the impact of papers produced by Johan Vertens. 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 Johan Vertens. The network helps show where Johan Vertens may publish in the future.
Co-authors
The 17 scholars most cited alongside Johan Vertens, 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 | 154 | |
| 2 | Long-Term Urban Vehicle Localization Using Pole Landmarks Extracted from 3-D Lidar Scans | 2019 | 56 |
| 3 | 2017 | 49 | |
| 4 | 2020 | 21 | |
| 5 | 2015 | 19 | |
| 6 | 2019 | 8 | |
| 7 | 2020 | 2 | |
| 8 | 2023 | 2 | |
| 9 | 2020 | 1 | |
| 10 | 2022 | 1 |
About Johan Vertens
Johan Vertens is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering, Aerospace Engineering, Environmental Engineering and Computer Graphics and Computer-Aided Design, having authored 10 papers that have together received 313 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (4 papers), Advanced Neural Network Applications (4 papers), Autonomous Vehicle Technology and Safety (3 papers), Advanced Image and Video Retrieval Techniques (2 papers), Remote Sensing and LiDAR Applications (2 papers), Advanced Vision and Imaging (2 papers), Vehicle Dynamics and Control Systems (1 paper) and Computer Graphics and Visualization Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (207 citations), Geology (39 citations), Aerospace Engineering (124 citations), Environmental Engineering (64 citations) and Automotive Engineering (46 citations). Johan Vertens has collaborated with scholars based in Germany and India. Frequent co-authors include Wolfram Burgard, Abhinav Valada, Lukas Luft, Alexander Schaefer, Daniel Buscher, Fabian Fischer, Albert Gollhofer, Rui Zhang, Leonhard Michael Reindl and Tayyab Naseer. Their work appears in journals such as Robotics and Autonomous Systems, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Springer proceedings in advanced robotics, IEEE Conference Proceedings and arXiv (Cornell University).
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.