Daniel Bartz
Impact in
- Automotive Engineering top 10%
- Autonomous Vehicle Technology and Safety
- Vehicle Dynamics and Control Systems
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- Robotic Path Planning Algorithms
- Advanced Vision and Imaging
Papers in
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- Blind Source Separation Techniques 2
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- Autonomous Vehicle Technology and Safety 2
- Co-authors
- Klaus- Robert Müller (4 shared papers)Stefan Haufe (1 shared paper)Irene Winkler (1 shared paper)Christian W. Hesse (1 shared paper)Johannes Höhne (2 shared papers)Benjamin Blankertz (2 shared papers)Steven Lemm (1 shared paper)Martin N. Hebart (1 shared paper)
- Journals
- PLoS ONE (1 paper)Springer tracts in advanced robotics (1 paper)Journal of Field Robotics (1 paper)NeuroImage (1 paper)IEEE Transactions on Signal Processing (1 paper)
- Partner nations
- GermanyUnited StatesSouth Korea
In The Last Decade
Daniel Bartz
6 papers receiving 303 citations
Peers
Comparison fields: 5 of 71
- Automotive Engineering 124
- Computer Vision and Pattern Recognition 161
- Aerospace Engineering 120
- Instrumentation 11
- Control and Systems Engineering 70
Countries citing papers authored by Daniel Bartz
This map shows the geographic impact of Daniel Bartz'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 Bartz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Bartz more than expected).
Fields of papers citing papers by Daniel Bartz
This network shows the impact of papers produced by Daniel Bartz. 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 Bartz. The network helps show where Daniel Bartz may publish in the future.
Co-authors
The 8 scholars most cited alongside Daniel Bartz, 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 | 2006 | 131 | |
| 2 | 2007 | 114 | |
| 3 | 2016 | 50 | |
| 4 | 2013 | 17 | |
| 5 | 2015 | 9 | |
| 6 | 2014 | 4 |
About Daniel Bartz
Daniel Bartz is a scholar working on Signal Processing, Automotive Engineering, Cognitive Neuroscience, Computer Vision and Pattern Recognition and Aerospace Engineering, having authored 6 papers that have together received 325 indexed citations. Recurring topics across this work include Blind Source Separation Techniques (2 papers), Robotic Path Planning Algorithms (2 papers), Neural dynamics and brain function (2 papers), Robotics and Sensor-Based Localization (2 papers), EEG and Brain-Computer Interfaces (2 papers), Autonomous Vehicle Technology and Safety (2 papers), Complex Systems and Time Series Analysis (1 paper) and Microwave Imaging and Scattering Analysis (1 paper). The work is most often cited by research in Automotive Engineering (124 citations), Computer Vision and Pattern Recognition (161 citations), Aerospace Engineering (120 citations), Instrumentation (11 citations) and Control and Systems Engineering (70 citations). Daniel Bartz has collaborated with scholars based in Germany, United States and South Korea. Frequent co-authors include Klaus- Robert Müller, Stefan Haufe, Irene Winkler, Christian W. Hesse, Johannes Höhne, Benjamin Blankertz, Steven Lemm and Martin N. Hebart. Their work appears in journals such as PLoS ONE, Springer tracts in advanced robotics, Journal of Field Robotics, NeuroImage and IEEE Transactions on Signal 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.