Stephan Liwicki

1.2k citations
18 papers · 366 · h-index 9

Impact in

    • Hand Gesture Recognition Systems
    • Human Pose and Action Recognition
    • Face and Expression Recognition
    • Video Surveillance and Tracking Methods
    • Advanced Image and Video Retrieval Techniques
    • Advanced Neural Network Applications
    • Advanced Vision and Imaging

Papers in

Stephan Liwicki

18 papers receiving 356 citations

Peers

Stephan Liwicki
Comparison fields: 5 of 56
  • Human-Computer Interaction 112
  • Computer Vision and Pattern Recognition 268
  • Developmental and Educational Psychology 73
  • Media Technology 33
  • Signal Processing 26
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Yuncheng Li China
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Citations per field
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Citations per year

Countries citing papers authored by Stephan Liwicki

Since Specialization
Citations

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

Fields of papers citing papers by Stephan Liwicki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 200989
2 201265
3 201949
4 201244
5 202131
6 200921
7 201520
8
ContextNet: Exploring Context and Detail for Semantic Segmentation in Real-time.
201814
9
Fast-SCNN: Fast Semantic Segmentation Network.
20199
10 20116
11 20176
12 20243
13 20142
14 20232
15 20202
16 20141
17 20241
18 20211

About Stephan Liwicki

Stephan Liwicki is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Signal Processing and Human-Computer Interaction, having authored 18 papers that have together received 366 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (6 papers), Robotics and Sensor-Based Localization (5 papers), Advanced Neural Network Applications (5 papers), Multimodal Machine Learning Applications (4 papers), Human Pose and Action Recognition (3 papers), Face and Expression Recognition (3 papers), Video Surveillance and Tracking Methods (3 papers) and Hand Gesture Recognition Systems (2 papers). The work is most often cited by research in Human-Computer Interaction (112 citations), Computer Vision and Pattern Recognition (268 citations), Developmental and Educational Psychology (73 citations), Media Technology (33 citations) and Signal Processing (26 citations). Stephan Liwicki has collaborated with scholars based in United Kingdom, Japan and Netherlands. Frequent co-authors include Mark Everingham, Stefanos Zafeiriou, Maja Pantić, Georgios Tzimiropoulos, Roberto Cipolla, Rudra P. K. Poudel, William A. P. Smith, Christopher Zach, Roberto Mecca and Sen He. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Image Processing, International Journal of Computer Vision, IEEE Robotics and Automation Letters and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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