Markus Stricker
- Computer Vision and Pattern Recognition top 0.5%
- Materials Chemistry top 10%
- Media Technology top 1%
- Mechanical Engineering top 10%
- Mechanics of Materials top 10%
- Co-authors
- Michael J. SwainD. WeygandGaudenz DanuserKatrin SchulzW.A. CurtinThomas HochrainerBinglun YinPeter Gumbsch
- Topics
- Microstructure and mechanical properties (15 papers)Metal and Thin Film Mechanics (6 papers)Machine Learning in Materials Science (5 papers)
- Journals
- Journal of Applied PhysicsIEEE Transactions on Pattern Analysis and Machine IntelligenceActa Materialia
- Partner nations
- GermanySwitzerlandAustria
In The Last Decade
Markus Stricker
36 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 112
- Computer Vision and Pattern Recognition 1.4k
- Materials Chemistry 359
- Media Technology 299
- Mechanical Engineering 220
- Mechanics of Materials 170
Countries citing papers authored by Markus Stricker
This map shows the geographic impact of Markus Stricker'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 Markus Stricker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Stricker more than expected).
Fields of papers citing papers by Markus Stricker
This network shows the impact of papers produced by Markus Stricker. 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 Markus Stricker. The network helps show where Markus Stricker may publish in the future.
Co-authorship network of co-authors of Markus Stricker
This figure shows the co-authorship network connecting the top 25 collaborators of Markus Stricker. A scholar is included among the top collaborators of Markus Stricker 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 Markus Stricker. Markus Stricker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 17 | |
| 7 | 4 | |
| 8 | 2 | |
| 9 | 2 | |
| 10 | 38 | |
| 11 | 56 | |
| 12 | 36 | |
| 13 | 54 | |
| 14 | 43 | |
| 15 | 3 | |
| 16 | 156 | |
| 17 | Similarity of color imagesbreakdown → | 1160 |
| 18 | The Capacity and the Sensitivity of Color Histogram Indexing | 22 |
| 19 | 4 | |
| 20 | written by the attendees of the NSF Active Vision Workshop) | 3 |
About Markus Stricker
Markus Stricker is a scholar working on Metals and Alloys, Structural Biology and Materials Chemistry, having authored 37 papers that have together received 2.0k indexed citations. Recurring topics across this work include Microstructure and mechanical properties (15 papers), Metal and Thin Film Mechanics (6 papers) and Machine Learning in Materials Science (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.4k citations), Media Technology (299 citations) and Signal Processing (124 citations). Markus Stricker has collaborated with scholars based in Germany, Switzerland and Austria. Frequent co-authors include Michael J. Swain, D. Weygand, Gaudenz Danuser, Katrin Schulz, W.A. Curtin, Thomas Hochrainer, Binglun Yin, Peter Gumbsch, Carsten Bonnekoh and Wolfgang Pantleon. Their work appears in journals such as Journal of Applied Physics, IEEE Transactions on Pattern Analysis and Machine Intelligence and Acta Materialia.
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.