Thomas Stiefmeier

1.4k citations
18 papers · 675 · h-index 12

Impact in

Papers in

Thomas Stiefmeier

18 papers receiving 636 citations

Peers

Thomas Stiefmeier
Comparison fields: 5 of 67
  • Human-Computer Interaction 173
  • Computer Vision and Pattern Recognition 471
  • Signal Processing 78
  • Artificial Intelligence 176
  • Computer Networks and Communications 113
Replace Georg Ogris with:
Georg Ogris Austria
Ju Shen United States
Charissa Ann Ronao South Korea
Jang‐Hee Yoo South Korea
Jaehong Kim South Korea
Jennifer Casper United States
Petr Novák Czechia
Víctor Escorcia Saudi Arabia
David J. Bruemmer United States
Miguel Hernando Spain
Thomas Stiefmeier relative to Georg Ogris Austria Georg Ogris's profile →
Citations per field
00.5×1.5×1.9×
Georg Ogris · 1×
Citations per year

Countries citing papers authored by Thomas Stiefmeier

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Stiefmeier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Thomas Stiefmeier, 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 Thomas Stiefmeier Line = papers co-authored together Thomas Stiefmeier links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2008251
2 200789
3 200669
4 200754
5 200542
6 200735
7 200827
8
Event-Based Activity Tracking in Work Environments
200622
9 200420
10
A Wearable Computing Prototype for supporting training activities in Automotive Production
200720
11 201114
12 201213
13 20147
14 20125
15 20113
16 20112
17 20111
18 20131

About Thomas Stiefmeier

Thomas Stiefmeier is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Human-Computer Interaction, Artificial Intelligence and Biomedical Engineering, having authored 18 papers that have together received 675 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (10 papers), Hand Gesture Recognition Systems (5 papers), Indoor and Outdoor Localization Technologies (5 papers), Gait Recognition and Analysis (3 papers), Speech and Audio Processing (2 papers), Augmented Reality Applications (2 papers), Human Pose and Action Recognition (2 papers) and Smart Grid Energy Management (2 papers). The work is most often cited by research in Human-Computer Interaction (173 citations), Computer Vision and Pattern Recognition (471 citations), Signal Processing (78 citations), Artificial Intelligence (176 citations) and Computer Networks and Communications (113 citations). Thomas Stiefmeier has collaborated with scholars based in Switzerland, Germany and Austria. Frequent co-authors include Daniel Roggen, Georg Ogris, Paul Lukowicz, Gerhard Tröster, Holger Junker, Piero Zappi, Luca Benini, Elisabetta Farella, H. Junker and Thorsten Staake. Their work appears in journals such as IEEE Pervasive Computing, Pattern Analysis and Applications, Computer Science and Information Systems, PubMed and Procedia Engineering.

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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