Daniel Gehrig
Impact in
- Acoustics and Ultrasonics top 10%
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- Advanced Neural Network Applications
- Advanced Vision and Imaging
- Advanced Image Processing Techniques
Papers in
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- Advanced Memory and Neural Computing 9
- Ferroelectric and Negative Capacitance Devices 4
- CCD and CMOS Imaging Sensors 3
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- Advanced Neural Network Applications 4
- Co-authors
- Davide Scaramuzza (19 shared papers)Henri Rebecq (4 shared papers)Guillermo Gallego (2 shared papers)Mathias Gehrig (6 shared papers)Nick Barnes (1 shared paper)Cedric Scheerlinck (1 shared paper)Robert Mahony (1 shared paper)Javier Hidalgo‐Carrió (2 shared papers)
- Journals
- IEEE Robotics and Automation Letters (3 papers)International Journal of Computer Vision (2 papers)Nature (1 paper)Cellular and Molecular Life Sciences (1 paper)IEEE Transactions on Image Processing (1 paper)
- Partner nations
- SwitzerlandUnited StatesChina
In The Last Decade
Daniel Gehrig
22 papers receiving 924 citations
Daniel Gehrig's Hit Papers
Peers
Comparison fields: 5 of 81
- Acoustics and Ultrasonics 21
- Computer Vision and Pattern Recognition 379
- Instrumentation 52
- Electrical and Electronic Engineering 479
- Cognitive Neuroscience 138
Countries citing papers authored by Daniel Gehrig
This map shows the geographic impact of Daniel Gehrig'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 Daniel Gehrig with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Gehrig more than expected).
Fields of papers citing papers by Daniel Gehrig
This network shows the impact of papers produced by Daniel Gehrig. 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 Daniel Gehrig. The network helps show where Daniel Gehrig may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Gehrig, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 150 | |
| 2 | 2020 | 139 | |
| 3 | 2018 | 131 | |
| 4 | 2021 | 97 | |
| 5 | 2022 | 86 | |
| 6 | Low-latency automotive vision with event cameras Hit paper breakdown → | 2024 | 82 |
| 7 | 2022 | 82 | |
| 8 | 2022 | 45 | |
| 9 | 2022 | 33 | |
| 10 | 2023 | 18 | |
| 11 | 2024 | 16 | |
| 12 | 2021 | 15 | |
| 13 | 2023 | 15 | |
| 14 | 1976 | 12 | |
| 15 | 2024 | 11 | |
| 16 | 2023 | 10 | |
| 17 | 2024 | 7 | |
| 18 | Video to Events: Bringing Modern Computer Vision Closer to Event Cameras. | 2019 | 6 |
| 19 | 2024 | 6 | |
| 20 | 2017 | 3 |
About Daniel Gehrig
Daniel Gehrig is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Aerospace Engineering, Radiation and Artificial Intelligence, having authored 23 papers that have together received 968 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (9 papers), Ferroelectric and Negative Capacitance Devices (4 papers), Advanced Neural Network Applications (4 papers), Robotics and Sensor-Based Localization (4 papers), Radiation Detection and Scintillator Technologies (3 papers), CCD and CMOS Imaging Sensors (3 papers), Atomic and Subatomic Physics Research (2 papers) and Age of Information Optimization (2 papers). The work is most often cited by research in Acoustics and Ultrasonics (21 citations), Computer Vision and Pattern Recognition (379 citations), Instrumentation (52 citations), Electrical and Electronic Engineering (479 citations) and Cognitive Neuroscience (138 citations). Daniel Gehrig has collaborated with scholars based in Switzerland, United States and China. Frequent co-authors include Davide Scaramuzza, Henri Rebecq, Guillermo Gallego, Mathias Gehrig, Nick Barnes, Cedric Scheerlinck, Robert Mahony, Javier Hidalgo‐Carrió, Stepan Tulyakov and Stamatios Georgoulis. Their work appears in journals such as IEEE Robotics and Automation Letters, International Journal of Computer Vision, Nature, Cellular and Molecular Life Sciences and IEEE Transactions on Image Processing.
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.