Michael Darms

22 papers receiving 505 citations

Peers

Michael Darms
Comparison fields: 5 of 54
  • Automotive Engineering 291
  • Computer Vision and Pattern Recognition 243
  • Instrumentation 20
  • Aerospace Engineering 140
  • Safety, Risk, Reliability and Quality 36
Replace Kyounghwan An with:
Kyounghwan An South Korea
C. Urmson United States
Seiya Maeda Japan
Tsun-Hsuan Wang United States
Isaac Miller United States
Yonghwan Jeong South Korea
Manuel Yguel France
Qian Meng China
W. Niehsen Germany
Olov Andersson Sweden
Michael Darms relative to Kyounghwan An South Korea Kyounghwan An's profile →
Citations per field
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Kyounghwan An · 1×
Citations per year

Countries citing papers authored by Michael Darms

Since Specialization
Citations

This map shows the geographic impact of Michael Darms'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 Michael Darms with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Darms more than expected).

Fields of papers citing papers by Michael Darms

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Darms. 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 Michael Darms. The network helps show where Michael Darms may publish in the future.

Co-authors

The 17 scholars most cited alongside Michael Darms, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Darms Line = papers co-authored together Michael Darms links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008104
2 2009103
3 200998
4 200871
5 200251
6 201034
7 200523
8 200712
9 20159
10 20107
11 20157
12 20075
13 20074
14 20103
15 20093
16 20073
17
Fusion von Umfelddaten für Fahrerassistenzsysteme
20032
18 20182
19 20112
20
Eine Systemarchitektur zur Fusion von Umfelddaten
20042

About Michael Darms

Michael Darms is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering and Control and Systems Engineering, having authored 22 papers that have together received 548 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (11 papers), Robotic Path Planning Algorithms (6 papers), Target Tracking and Data Fusion in Sensor Networks (6 papers), Robotics and Sensor-Based Localization (4 papers), Risk and Safety Analysis (2 papers), Human-Automation Interaction and Safety (2 papers), Anomaly Detection Techniques and Applications (2 papers) and Vehicle Dynamics and Control Systems (2 papers). The work is most often cited by research in Automotive Engineering (291 citations), Computer Vision and Pattern Recognition (243 citations), Instrumentation (20 citations), Aerospace Engineering (140 citations) and Safety, Risk, Reliability and Quality (36 citations). Michael Darms has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Paul E. Rybski, Chris Urmson, Dave Ferguson, C. Urmson, Sascha Kolski, Christopher Baker, Hermann Winner, Rolf Schuhmann, T. Weiland and John M. Dolan. Their work appears in journals such as AI Magazine, IEEE Microwave and Wireless Components Letters, IEEE Transactions on Intelligent Transportation Systems, ATZ - Automobiltechnische Zeitschrift and SAE International journal of passenger cars. Electronic and electrical systems.

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.

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