Markus Krause
Impact in
- Dermatology top 2%
- Hidradenitis Suppurativa and Treatments
- Dermatology and Skin Diseases
-
- Mobile Crowdsensing and Crowdsourcing
- Open Source Software Innovations
Papers in
-
- Data Stream Mining Techniques 4
- Natural Language Processing Techniques 3
- Artificial Intelligence in Games 2
-
- Mobile Crowdsensing and Crowdsourcing 10
- Open Source Software Innovations 5
- Online Learning and Analytics 4
- Co-authors
- Sylke Schneider‐Burrus (2 shared papers)Wolfram Sterry (2 shared papers)Ellen Witte (1 shared paper)Stefanie Kunz (1 shared paper)Hans‐Dieter Volk (1 shared paper)Katarzyna Warszawska (1 shared paper)Katrin Witte (1 shared paper)Ansgar Lukowsky (1 shared paper)
- Journals
- The Journal of Immunology (1 paper)IEEE Transactions on Learning Technologies (1 paper)JDDG Journal der Deutschen Dermatologischen Gesellschaft (1 paper)AI Magazine (1 paper)IEEE Access (1 paper)
- Partner nations
- GermanyUnited StatesIreland
In The Last Decade
Markus Krause
23 papers receiving 420 citations
Peers
Comparison fields: 5 of 74
- Dermatology 210
- Computer Science Applications 124
- Human-Computer Interaction 26
- Surgery 133
- Epidemiology 85
Countries citing papers authored by Markus Krause
This map shows the geographic impact of Markus Krause'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 Krause with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Krause more than expected).
Fields of papers citing papers by Markus Krause
This network shows the impact of papers produced by Markus Krause. 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 Krause. The network helps show where Markus Krause may publish in the future.
Co-authors
The 25 scholars most cited alongside Markus Krause, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 206 | |
| 2 | 2010 | 36 | |
| 3 | 2017 | 34 | |
| 4 | 2007 | 30 | |
| 5 | 2016 | 13 | |
| 6 | 2011 | 12 | |
| 7 | 2016 | 11 | |
| 8 | Predicting Crowd-Based Translation Quality with Language-Independent Feature Vectors. | 2012 | 10 |
| 9 | 2014 | 9 | |
| 10 | 2014 | 9 | |
| 11 | 2015 | 9 | |
| 12 | 2015 | 8 | |
| 13 | 2015 | 8 | |
| 14 | 2010 | 8 | |
| 15 | 2016 | 5 | |
| 16 | 2009 | 5 | |
| 17 | 2013 | 4 | |
| 18 | 2018 | 4 | |
| 19 | 2017 | 3 | |
| 20 | 2019 | 2 |
About Markus Krause
Markus Krause is a scholar working on Artificial Intelligence, Computer Science Applications, Information Systems, Computer Vision and Pattern Recognition and Safety Research, having authored 23 papers that have together received 430 indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (10 papers), Open Source Software Innovations (5 papers), Online Learning and Analytics (4 papers), Data Stream Mining Techniques (4 papers), Natural Language Processing Techniques (3 papers), Data Visualization and Analytics (3 papers), Artificial Intelligence in Games (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Dermatology (210 citations), Computer Science Applications (124 citations), Human-Computer Interaction (26 citations), Surgery (133 citations) and Epidemiology (85 citations). Markus Krause has collaborated with scholars based in Germany, United States and Ireland. Frequent co-authors include Sylke Schneider‐Burrus, Wolfram Sterry, Ellen Witte, Stefanie Kunz, Hans‐Dieter Volk, Katarzyna Warszawska, Katrin Witte, Ansgar Lukowsky, Conny Hoeflich and Robert Sabat. Their work appears in journals such as The Journal of Immunology, IEEE Transactions on Learning Technologies, JDDG Journal der Deutschen Dermatologischen Gesellschaft, AI Magazine and IEEE Access.
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.