Beat Flepp
Impact in
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety
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- Advanced Neural Network Applications
- Robotic Path Planning Algorithms
- Video Surveillance and Tracking Methods
- Advanced Vision and Imaging
Papers in
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- Robotic Path Planning Algorithms 3
- Video Surveillance and Tracking Methods 2
- Multimodal Machine Learning Applications 1
- Advanced Neural Network Applications 1
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- Robotics and Sensor-Based Localization 4
- Co-authors
- Urs Müller (4 shared papers)Jan Ben (3 shared papers)Eric Cosatto (1 shared paper)Y. Le Cun (1 shared paper)Yann LeCun (3 shared papers)Raia Hadsell (2 shared papers)Pierre Sermanet (2 shared papers)Lawrence D. Jackel (1 shared paper)
- Journals
- Neural Information Processing Systems (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1 paper)IFAC Proceedings Volumes (1 paper)The MIT Press eBooks (1 paper)
- Partner nations
- United States
In The Last Decade
Beat Flepp
4 papers receiving 302 citations
Peers
Comparison fields: 5 of 56
- Automotive Engineering 136
- Computer Vision and Pattern Recognition 211
- Artificial Intelligence 116
- Aerospace Engineering 79
- Control and Systems Engineering 62
Countries citing papers authored by Beat Flepp
This map shows the geographic impact of Beat Flepp'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 Beat Flepp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beat Flepp more than expected).
Fields of papers citing papers by Beat Flepp
This network shows the impact of papers produced by Beat Flepp. 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 Beat Flepp. The network helps show where Beat Flepp may publish in the future.
Co-authors
The 9 scholars most cited alongside Beat Flepp, 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 | Off-Road Obstacle Avoidance through End-to-End Learning | 2005 | 306 |
| 2 | 2008 | 8 | |
| 3 | 2007 | 7 | |
| 4 | 2013 | 6 |
About Beat Flepp
Beat Flepp is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Computer Networks and Communications, Infectious Diseases and Organic Chemistry, having authored 4 papers that have together received 327 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (4 papers), Robotic Path Planning Algorithms (3 papers), Video Surveillance and Tracking Methods (2 papers), Multimodal Machine Learning Applications (1 paper), Distributed Control Multi-Agent Systems (1 paper) and Advanced Neural Network Applications (1 paper). The work is most often cited by research in Automotive Engineering (136 citations), Computer Vision and Pattern Recognition (211 citations), Artificial Intelligence (116 citations), Aerospace Engineering (79 citations) and Control and Systems Engineering (62 citations). Beat Flepp has collaborated with scholars based in United States. Frequent co-authors include Urs Müller, Jan Ben, Eric Cosatto, Y. Le Cun, Yann LeCun, Raia Hadsell, Pierre Sermanet, Lawrence D. Jackel and Jefferson Y. Han. Their work appears in journals such as Neural Information Processing Systems, Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE, IFAC Proceedings Volumes and The MIT Press eBooks.
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.