Korbinian Frank

808 total citations
26 papers, 366 citations indexed

About

Korbinian Frank is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Korbinian Frank has authored 26 papers receiving a total of 366 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 17 papers in Artificial Intelligence and 9 papers in Signal Processing. Recurrent topics in Korbinian Frank's work include Context-Aware Activity Recognition Systems (18 papers), Bayesian Modeling and Causal Inference (9 papers) and Data Management and Algorithms (5 papers). Korbinian Frank is often cited by papers focused on Context-Aware Activity Recognition Systems (18 papers), Bayesian Modeling and Causal Inference (9 papers) and Data Management and Algorithms (5 papers). Korbinian Frank collaborates with scholars based in Germany, Spain and Ireland. Korbinian Frank's co-authors include Patrick Robertson, Thomas Strang, Tom Pfeifer, Matthias Röckl, Michael Angermann, Bernhard Krach, Andreas Lehner, Claudia Linnhoff‐Popien, Daqing Zhang and Dingqi Yang and has published in prestigious journals such as Personal and Ubiquitous Computing, Journal of Intensive Care and DSpace - NTUA (National Technical University of Athens).

In The Last Decade

Korbinian Frank

26 papers receiving 334 citations

Peers

Korbinian Frank
Comparison fields: 5 of 59
  • Computer Vision and Pattern Recognition 189
  • Electrical and Electronic Engineering 133
  • Computer Networks and Communications 105
  • Artificial Intelligence 79
  • Biomedical Engineering 78
Replace Seon-Woo Lee with:
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Citations per field, relative to Korbinian Frank
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Citations per year, relative to Korbinian Frank
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Countries citing papers authored by Korbinian Frank

Since Specialization
Citations

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

Fields of papers citing papers by Korbinian Frank

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Korbinian Frank

This figure shows the co-authorship network connecting the top 25 collaborators of Korbinian Frank. A scholar is included among the top collaborators of Korbinian Frank 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 Korbinian Frank. Korbinian Frank is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 37
2 17
3 11
4 2
5
Reliable Real-Time Recognition of motion related human activities using MEMS inertial sensors
44
6 2
7
Towards Pervasive Smart Spaces: A Tale of Two Projects
3
8 71
9 12
10
How to make Personal Smart Spaces Context-aware
5
11 4
12 3
13 2
14 9
15 4
16 36
17 11
18 2
19
Integration Issues of an Ontology based Context Modelling Approach
2
20
Applications of a Context Ontology Language
22

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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