Daniel Kerpen

442 citations
21 papers · 243 · h-index 6

Impact in

Papers in

Daniel Kerpen

19 papers receiving 235 citations

Peers

Daniel Kerpen
Comparison fields: 5 of 53
  • Computer Networks and Communications 136
  • Information Systems 93
  • Industrial and Manufacturing Engineering 39
  • Artificial Intelligence 63
  • Signal Processing 19
Replace Yaser Alhasawi with:
Yaser Alhasawi Saudi Arabia
Salem Alghamdi Saudi Arabia
Meghna Manoj Nair India
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Abdelrahman H. Hussein Jordan
Oleksiy Khriyenko Finland
Stijn Verstichel Belgium
G. Ayorkor Mills-Tettey United States
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Ike Kunze Germany
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Kerpen

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Kerpen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Daniel Kerpen, 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 Daniel Kerpen Line = papers co-authored together Daniel Kerpen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015164
2 201419
3 201618
4 20168
5 20167
6
Influence of human factors on cognitive textile production
20155
7 20183
8 20173
9 20173
10 20202
11 20142
12 20162
13 20171
14 20211
15 20191
16 20151
17
Anforderungskatalog für Assistenzsysteme 4.0 an Textilmaschinen am Beispiel einer Webmaschine
20161
18
Intelligent assistance systems for industrial textile work environments
20161
19 20201
20 20170

About Daniel Kerpen

Daniel Kerpen is a scholar working on Sociology and Political Science, Management of Technology and Innovation, Information Systems, Computer Vision and Pattern Recognition and Human-Computer Interaction, having authored 21 papers that have together received 243 indexed citations. Recurring topics across this work include Digital Innovation in Industries (5 papers), Innovation, Technology, and Society (4 papers), Privacy, Security, and Data Protection (4 papers), Design Education and Practice (2 papers), Digital Transformation in Industry (2 papers), Persona Design and Applications (2 papers), IoT and Edge/Fog Computing (2 papers) and Public Administration and Political Analysis (2 papers). The work is most often cited by research in Computer Networks and Communications (136 citations), Information Systems (93 citations), Industrial and Manufacturing Engineering (39 citations), Artificial Intelligence (63 citations) and Signal Processing (19 citations). Daniel Kerpen has collaborated with scholars based in Germany and United States. Frequent co-authors include Klaus Wehrle, Roger Häußling, Martin Henze, Bernhard Rumpe⋆, Yves-Simon Gloy, Michael Eggert, René Hummen, Antonio Pérez, J. M. Conrad and Thomas Gries. Their work appears in journals such as Future Generation Computer Systems, Lecture notes in computer science, Communications in computer and information science, RWTH Publications (RWTH Aachen) and Open MIND.

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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