Stephan Sigg

3.1k citations
132 papers · 2.1k · 1 hit paper · h-index 22

Impact in

Papers in

Stephan Sigg

125 papers receiving 2.0k citations

Stephan Sigg's Hit Papers

Privacy‐preserving federated learning based on multi‐key homomorphic encryption 2022 · 222 citations
2220+1+2Years since publication50100150200

Peers

Stephan Sigg
Comparison fields: 5 of 99
  • Signal Processing 446
  • Human-Computer Interaction 203
  • Computer Vision and Pattern Recognition 556
  • Computer Networks and Communications 598
  • Electrical and Electronic Engineering 1.2k
Replace Parth H. Pathak with:
Parth H. Pathak United States
Chenren Xu China
Kun Qian China
Longfei Shangguan United States
Wei Xi China
Anthony Rowe United States
Xianping Tao China
Shuochao Yao United States
Hongkai Wen United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Stephan Sigg

Since Specialization
Citations

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

Fields of papers citing papers by Stephan Sigg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Stephan Sigg, 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 Stephan Sigg Line = papers co-authored together Stephan Sigg links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 132 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Privacy‐preserving federated learning based on multi‐key homomorphic encryption
Hit paper breakdown →
2022222
2 2013204
3 2011125
4 2018116
5 2021111
6 2014102
7 2019101
8 201698
9 201387
10 202253
11 201043
12 201333
13 201931
14 201831
15
Challenges for device-free radio-based activity recognition
201130
16 201628
17 201427
18 201227
19 201926
20 201222

About Stephan Sigg

Stephan Sigg is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing and Biomedical Engineering, having authored 132 papers that have together received 2.1k indexed citations. Recurring topics across this work include Indoor and Outdoor Localization Technologies (42 papers), Context-Aware Activity Recognition Systems (28 papers), Speech and Audio Processing (19 papers), User Authentication and Security Systems (16 papers), Cooperative Communication and Network Coding (12 papers), Advanced MIMO Systems Optimization (9 papers), Bluetooth and Wireless Communication Technologies (9 papers) and Music and Audio Processing (8 papers). The work is most often cited by research in Signal Processing (446 citations), Human-Computer Interaction (203 citations), Computer Vision and Pattern Recognition (556 citations), Computer Networks and Communications (598 citations) and Electrical and Electronic Engineering (1.2k citations). Stephan Sigg has collaborated with scholars based in Finland, Germany and Japan. Frequent co-authors include Yusheng Ji, Shuyu Shi, Michael Beigl, Si‐Ahmed Naas, Jing Ma, Xixiang Lyu, Markus Scholz, Sameera Palipana, Ulf Blanke and Gerhard Tröster. Their work appears in journals such as IEEE Transactions on Mobile Computing, IEEE Access, IEEE Pervasive Computing, IEEE Internet of Things Journal and IEEE Sensors Journal.

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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