Clemens Eppner

31 papers receiving 1.2k citations

Clemens Eppner's Hit Papers

Deep Learning Approaches to Grasp Synthesis: A Review 2023 · 155 citations
1550+1+2Years since publication50100150

Peers

Clemens Eppner
Comparison fields: 5 of 77
  • Control and Systems Engineering 928
  • Human-Computer Interaction 119
  • Computer Vision and Pattern Recognition 421
  • Biomedical Engineering 489
  • Aerospace Engineering 192
Replace Steffen Knoop with:
Steffen Knoop Germany
Kuan‐Ting Yu United States
Renaud J. Detry Belgium
Nikhil Chavan-Dafle United States
Michael Danielczuk United States
Aaron Walsman United States
Matthew Matl United States
Kaiyu Hang United States
Jacky Liang United States
Nima Fazeli United States
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Citations per field
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Citations per year

Countries citing papers authored by Clemens Eppner

Since Specialization
Citations

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

Fields of papers citing papers by Clemens Eppner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Clemens Eppner, 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 Clemens Eppner Line = papers co-authored together Clemens Eppner links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015164
2
Deep Learning Approaches to Grasp Synthesis: A Review
Hit paper breakdown →
2023155
3 2020145
4 2016115
5 2016101
6 200991
7 201655
8 201749
9 201345
10 201544
11 201629
12 200929
13 202227
14 201827
15 201926
16 201925
17 201625
18 202223
19 201519
20 201716

About Clemens Eppner

Clemens Eppner is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Human-Computer Interaction, Artificial Intelligence and Biomedical Engineering, having authored 31 papers that have together received 1.3k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (25 papers), Reinforcement Learning in Robotics (7 papers), Modular Robots and Swarm Intelligence (6 papers), Robotic Path Planning Algorithms (6 papers), Human Pose and Action Recognition (6 papers), Soft Robotics and Applications (5 papers), Hand Gesture Recognition Systems (4 papers) and Robotics and Sensor-Based Localization (4 papers). The work is most often cited by research in Control and Systems Engineering (928 citations), Human-Computer Interaction (119 citations), Computer Vision and Pattern Recognition (421 citations), Biomedical Engineering (489 citations) and Aerospace Engineering (192 citations). Clemens Eppner has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Oliver Brock, Dieter Fox, Arsalan Mousavian, Roberto Martín-Martín, Marianne Maertens, Raphael Deimel, Sebastian Höfer, Rico Jonschkowski, Pieter Abbeel and Abhishek Gupta. Their work appears in journals such as The International Journal of Robotics Research, Springer tracts in advanced robotics, IEEE Transactions on Robotics, IEEE Robotics and Automation Letters and Autonomous Robots.

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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