Stefan Mathe
Impact in
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- Visual Attention and Saliency Detection
- Image and Video Quality Assessment
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Multimodal Machine Learning Applications
- Video Surveillance and Tracking Methods
- Human-Computer Interaction top 5%
- Gaze Tracking and Assistive Technology
Papers in
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- Visual Attention and Saliency Detection 3
- Multimodal Machine Learning Applications 2
- Video Analysis and Summarization 1
- Advanced Image and Video Retrieval Techniques 1
- Advanced Neural Network Applications 1
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- Gaze Tracking and Assistive Technology 2
- Co-authors
- Cristian Sminchisescu (4 shared papers)Afsaneh Fazly (1 shared paper)Sven Dickinson (1 shared paper)Suzanne Stevenson (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Journal of Vision (1 paper)Lund University Publications (Lund University) (1 paper)
In The Last Decade
Stefan Mathe
5 papers receiving 260 citations
Peers
Comparison fields: 5 of 44
- Computer Vision and Pattern Recognition 234
- Human-Computer Interaction 55
- Sensory Systems 14
- Artificial Intelligence 59
- Cognitive Neuroscience 29
Countries citing papers authored by Stefan Mathe
This map shows the geographic impact of Stefan Mathe'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 Stefan Mathe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Mathe more than expected).
Fields of papers citing papers by Stefan Mathe
This network shows the impact of papers produced by Stefan Mathe. 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 Stefan Mathe. The network helps show where Stefan Mathe may publish in the future.
Co-authors
The 4 scholars most cited alongside Stefan Mathe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 129 | |
| 2 | 2016 | 96 | |
| 3 | Action from Still Image Dataset and Inverse Optimal Control to Learn Task Specific Visual Scanpaths | 2013 | 32 |
| 4 | 2014 | 5 | |
| 5 | 2008 | 4 |
About Stefan Mathe
Stefan Mathe is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Infectious Diseases, having authored 5 papers that have together received 266 indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (3 papers), Gaze Tracking and Assistive Technology (2 papers), Multimodal Machine Learning Applications (2 papers), Domain Adaptation and Few-Shot Learning (1 paper), Video Analysis and Summarization (1 paper), Advanced Image and Video Retrieval Techniques (1 paper), Retinal Imaging and Analysis (1 paper) and Advanced Neural Network Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (234 citations), Human-Computer Interaction (55 citations), Sensory Systems (14 citations), Artificial Intelligence (59 citations) and Cognitive Neuroscience (29 citations). Stefan Mathe has collaborated with scholars based in Canada, Sweden and Romania. Frequent co-authors include Cristian Sminchisescu, Afsaneh Fazly, Sven Dickinson and Suzanne Stevenson. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Vision and Lund University Publications (Lund University).
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.