Phillip Karle
Impact in
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety
- Vehicle Dynamics and Control Systems
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- Advanced Neural Network Applications
- Robotic Path Planning Algorithms
- Video Surveillance and Tracking Methods
Papers in
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- Autonomous Vehicle Technology and Safety 9
- Vehicle Dynamics and Control Systems 2
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- Advanced Neural Network Applications 2
- Co-authors
- Markus Lienkamp (7 shared papers)Johannes Betz (8 shared papers)Maximilian Geisslinger (4 shared papers)Felix Nobis (2 shared papers)Ehsan Shafiei (1 shared paper)Boris Lohmann (1 shared paper)Leonhard Hermansdorfer (1 shared paper)Thomas Herrmann (1 shared paper)
- Journals
- IEEE Access (2 papers)IEEE Transactions on Intelligent Transportation Systems (1 paper)IEEE Transactions on Intelligent Vehicles (1 paper)Applied Sciences (1 paper)Journal of Field Robotics (1 paper)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Phillip Karle
12 papers receiving 208 citations
Peers
Comparison fields: 5 of 40
- Automotive Engineering 129
- Computer Vision and Pattern Recognition 79
- Control and Systems Engineering 49
- Instrumentation 7
- Software 7
Countries citing papers authored by Phillip Karle
This map shows the geographic impact of Phillip Karle'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 Phillip Karle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phillip Karle more than expected).
Fields of papers citing papers by Phillip Karle
This network shows the impact of papers produced by Phillip Karle. 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 Phillip Karle. The network helps show where Phillip Karle may publish in the future.
Co-authors
The 18 scholars most cited alongside Phillip Karle, 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 | 2022 | 60 | |
| 2 | 2023 | 41 | |
| 3 | 2021 | 35 | |
| 4 | 2023 | 30 | |
| 5 | 2021 | 18 | |
| 6 | 2023 | 12 | |
| 7 | 2024 | 4 | |
| 8 | 2023 | 4 | |
| 9 | 2023 | 4 | |
| 10 | 2020 | 4 | |
| 11 | 2023 | 1 | |
| 12 | 2022 | 1 |
About Phillip Karle
Phillip Karle is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering and Safety, Risk, Reliability and Quality, having authored 12 papers that have together received 214 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (9 papers), Anomaly Detection Techniques and Applications (2 papers), Vehicle Dynamics and Control Systems (2 papers), Traffic control and management (2 papers), Traffic and Road Safety (2 papers), Advanced Neural Network Applications (2 papers), Robotics and Sensor-Based Localization (2 papers) and Hydraulic and Pneumatic Systems (1 paper). The work is most often cited by research in Automotive Engineering (129 citations), Computer Vision and Pattern Recognition (79 citations), Control and Systems Engineering (49 citations), Instrumentation (7 citations) and Software (7 citations). Phillip Karle has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Markus Lienkamp, Johannes Betz, Maximilian Geisslinger, Felix Nobis, Ehsan Shafiei, Boris Lohmann, Leonhard Hermansdorfer, Thomas Herrmann, Alexander Heilmeier and Tim Stahl. Their work appears in journals such as IEEE Access, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Intelligent Vehicles, Applied Sciences and Journal of Field Robotics.
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.