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Researcher · Daimler (Germany) · Germany

Stefan K. Gehrig

Stefan K. Gehrig publishes mostly in Computer Vision and Pattern Recognition, Automotive Engineering and Aerospace Engineering, on topics such as Advanced Vision and Imaging, Autonomous Vehicle Technology and Safety and Robotics and Sensor-Based Localization.

ORCID 0000-0002-5270-9578 OpenAlex
World rank
#397,290
of 7,710,434 ranked researchers
Rank in Germany
#19,544
of 364,343
Works
83
Citations
2.1k
Citations per work
24.7
h-index
22
i10-index 41Top 11% in Computer Vision and Pattern Recognition
Stefan K. Gehrig

What does Stefan K. Gehrig research?

Stefan K. Gehrig's work is mostly in Computer Science (34%), Engineering (15%), Physics and Astronomy (5%).

Physical Sciences: 45 works · 54.0% of their workComputer Science: 28 works · 34.2% of their workComputer Vision and Pattern Recognition: 28 works · 34.2% of their workEngineering: 13 works · 15.2% of their workAutomotive Engineering: 7 works · 8.4% of their workAerospace Engineering: 6 works · 6.8% of their workPhysics and Astronomy: 4 works · 4.6% of their workNuclear and High Energy Physics: 4 works · 4.6% of their workEverything else: 32 works · 38.4% of their workSocial Sciences: 6 works · 7.6% of their workEconomics, Econometrics and Finance: 3 works · 3.8% of their workEconomics and Econometrics: 3 works · 3.8% of their workSocial Sciences: 3 works · 3.8% of their workSociology and Political Science: 3 works · 3.8% of their workTHEIR WORKStefan K. Gehrig83works
Physical Sciences54%Social Sciences8%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science2834.2%
    2. Engineering1315.2%
    3. Physics and Astronomy44.6%
  2. Everything else3238.4%
    1. Economics, Econometrics and Finance33.8%
    2. Social Sciences33.8%
  1. 1Computer Vision and Pattern Recognition34% of their works
  2. 2Automotive Engineering8% of their works
  3. 3Aerospace Engineering7% of their works
  4. 4Nuclear and High Energy Physics5% of their works
  5. 5Sociology and Political Science4% of their works
  6. 6Economics and Econometrics4% of their works

Research topics

Which keywords describe Stefan K. Gehrig's research?

The keywords of their largest research topics: Deep Learning, Convolutional Networks, Depth Estimation, Optical Flow, Stereo Vision, Autonomous Vehicles, Collision Avoidance and Convolutional Neural Networks.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 23 words, with their numbers
  1. Deep Learning464 topics
  2. Convolutional Networks392 topics
  3. Depth Estimation392 topics
  4. Optical Flow311 topic
  5. Stereo Vision311 topic
  6. Autonomous Vehicles262 topics
  7. Collision Avoidance262 topics
  8. Convolutional Neural Networks192 topics
  9. Driver Assistance Systems191 topic
  10. Trajectory Prediction191 topic
  11. 3D Mapping161 topic
  12. Neural Networks162 topics
  13. SLAM161 topic
  14. Object Tracking111 topic
  15. Visual Tracking111 topic
  16. Autofocusing81 topic
  17. Image81 topic
  18. Image Recognition81 topic
  19. Microscopy81 topic
  20. Object Detection81 topic
  21. Super-Resolution81 topic
  22. Optimal Motion Planning71 topic
  23. Sampling-Based Algorithms71 topic

Where does Stefan K. Gehrig work?

Stefan K. Gehrig's main affiliation in the publication record is Daimler (Germany), Germany.

How many publications and citations does Stefan K. Gehrig have?

OpenAlex counts 83 works and 2,053 citations for Stefan K. Gehrig, an h-index of 22, ranking #397,290 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

Discussion

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