Stefan Mathe
Impact in
-
- 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
- Video Surveillance and Tracking Methods
- Multimodal Machine Learning Applications
- Human-Computer Interaction top 10%
- Gaze Tracking and Assistive Technology
Papers in
-
- Visual Attention and Saliency Detection 3
- Multimodal Machine Learning Applications 2
- Advanced Image and Video Retrieval Techniques 1
- Video Analysis and Summarization 1
- Human Pose and Action Recognition 1
- Advanced Neural Network Applications 1
-
- Gaze Tracking and Assistive Technology 2
- Co-authors
- Cristian Sminchisescu (4 shared papers)Suzanne Stevenson (1 shared paper)Afsaneh Fazly (1 shared paper)Sven Dickinson (1 shared paper)
- Journals
- Journal of Vision (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Lund University Publications (Lund University) (1 paper)
In The Last Decade
Stefan Mathe
5 papers receiving 259 citations
Peers
Comparison fields: 5 of 44
- Computer Vision and Pattern Recognition 233
- Human-Computer Interaction 54
- 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 | 95 | |
| 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 265 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), Advanced Image and Video Retrieval Techniques (1 paper), Video Analysis and Summarization (1 paper), Human Pose and Action Recognition (1 paper), Advanced Neural Network Applications (1 paper) and Retinal Imaging and Analysis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (233 citations), Human-Computer Interaction (54 citations), Sensory Systems (14 citations), Artificial Intelligence (59 citations) and Cognitive Neuroscience (29 citations). Stefan Mathe has collaborated with scholars based in Sweden, Canada and Romania. Frequent co-authors include Cristian Sminchisescu, Suzanne Stevenson, Afsaneh Fazly and Sven Dickinson. Their work appears in journals such as Journal of Vision, IEEE Transactions on Pattern Analysis and Machine Intelligence 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.