Richard Meyes
- Industrial and Manufacturing Engineering top 5%
- Artificial Intelligence
- Control and Systems Engineering
- Computer Vision and Pattern Recognition
- Mechanical Engineering
- Co-authors
- Tobias MeisenThomas ThieleSabina JeschkeHasan TercanChristian BüscherChristian BrecherG. HirtChristian Hopmann
- Topics
- Industrial Vision Systems and Defect Detection (4 papers)Time Series Analysis and Forecasting (3 papers)Reinforcement Learning in Robotics (3 papers)
- Cited by
- Industrial and Manufacturing EngineeringComputer Vision and Pattern RecognitionControl and Systems Engineering
- Journals
- SHILAP Revista de lepidopterologíaApplied SciencesInternational Journal of Energy Research
In The Last Decade
Richard Meyes
17 papers receiving 238 citations
Peers
Comparison fields: 5 of 58
- Industrial and Manufacturing Engineering 104
- Artificial Intelligence 54
- Control and Systems Engineering 52
- Computer Vision and Pattern Recognition 46
- Mechanical Engineering 42
Countries citing papers authored by Richard Meyes
This map shows the geographic impact of Richard Meyes'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 Richard Meyes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard Meyes more than expected).
Fields of papers citing papers by Richard Meyes
This network shows the impact of papers produced by Richard Meyes. 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 Richard Meyes. The network helps show where Richard Meyes may publish in the future.
Co-authorship network of co-authors of Richard Meyes
This figure shows the co-authorship network connecting the top 25 collaborators of Richard Meyes. A scholar is included among the top collaborators of Richard Meyes based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Richard Meyes. Richard Meyes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 23 | |
| 6 | 0 | |
| 7 | 8 | |
| 8 | 6 | |
| 9 | 21 | |
| 10 | 10 | |
| 11 | 31 | |
| 12 | 0 | |
| 13 | 1 | |
| 14 | 4 | |
| 15 | 33 | |
| 16 | 24 | |
| 17 | 11 | |
| 18 | 13 | |
| 19 | 54 | |
| 20 | Emulation of Bursting Neurons in Neuromorphic Hardware Based on Phase-Change Materials | 1 |
About Richard Meyes
Richard Meyes is a scholar working on Industrial and Manufacturing Engineering, Health Informatics and Signal Processing, having authored 20 papers that have together received 245 indexed citations. Recurring topics across this work include Industrial Vision Systems and Defect Detection (4 papers), Time Series Analysis and Forecasting (3 papers) and Reinforcement Learning in Robotics (3 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (104 citations), Computer Vision and Pattern Recognition (46 citations) and Control and Systems Engineering (52 citations). Richard Meyes has collaborated with scholars based in Germany and Finland. Frequent co-authors include Tobias Meisen, Thomas Thiele, Sabina Jeschke, Hasan Tercan, Christian Büscher, Christian Brecher, G. Hirt, Christian Hopmann, Gerhard Lakemeyer and Pekka Abrahamsson. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Sciences and International Journal of Energy Research.
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.