Matei Mancaş
Impact in
- Sensory Systems top 2%
- Olfactory and Sensory Function Studies
- Human-Computer Interaction top 2%
- Gaze Tracking and Assistive Technology
Papers in
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- Visual Attention and Saliency Detection 22
- Advanced Image and Video Retrieval Techniques 11
- Image and Video Quality Assessment 9
- Video Surveillance and Tracking Methods 8
- Medical Image Segmentation Techniques 7
- Advanced Vision and Imaging 6
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- Gaze Tracking and Assistive Technology 10
- Co-authors
- Bernard Gosselin (35 shared papers)Nicolas Riche (14 shared papers)Thierry Dutoit (11 shared papers)Matthieu Duvinage (2 shared papers)Benoı̂t Macq (5 shared papers)Radu-Daniel Vatavu (2 shared papers)Benoît Macq (6 shared papers)John G. Taylor (2 shared papers)
In The Last Decade
Matei Mancaş
48 papers receiving 724 citations
Peers
Comparison fields: 5 of 96
- Sensory Systems 143
- Human-Computer Interaction 165
- Computer Vision and Pattern Recognition 584
- Cognitive Neuroscience 164
- Neurology 42
Countries citing papers authored by Matei Mancaş
This map shows the geographic impact of Matei Mancaş'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 Matei Mancaş with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matei Mancaş more than expected).
Fields of papers citing papers by Matei Mancaş
This network shows the impact of papers produced by Matei Mancaş. 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 Matei Mancaş. The network helps show where Matei Mancaş may publish in the future.
Co-authors
The 25 scholars most cited alongside Matei Mancaş, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 166 | |
| 2 | 2013 | 123 | |
| 3 | 2005 | 97 | |
| 4 | 2012 | 41 | |
| 5 | 2011 | 36 | |
| 6 | 2017 | 26 | |
| 7 | 2014 | 25 | |
| 8 | 2006 | 24 | |
| 9 | 2016 | 21 | |
| 10 | 2006 | 21 | |
| 11 | 2004 | 19 | |
| 12 | 2023 | 15 | |
| 13 | 2017 | 12 | |
| 14 | 2007 | 12 | |
| 15 | 2016 | 10 | |
| 16 | 2015 | 9 | |
| 17 | 2018 | 9 | |
| 18 | 2003 | 8 | |
| 19 | 2013 | 8 | |
| 20 | 2006 | 7 |
About Matei Mancaş
Matei Mancaş is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Artificial Intelligence, Sensory Systems and Cognitive Neuroscience, having authored 57 papers that have together received 760 indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (22 papers), Advanced Image and Video Retrieval Techniques (11 papers), Gaze Tracking and Assistive Technology (10 papers), Image and Video Quality Assessment (9 papers), Video Surveillance and Tracking Methods (8 papers), Medical Image Segmentation Techniques (7 papers), Olfactory and Sensory Function Studies (7 papers) and Advanced Vision and Imaging (6 papers). The work is most often cited by research in Sensory Systems (143 citations), Human-Computer Interaction (165 citations), Computer Vision and Pattern Recognition (584 citations), Cognitive Neuroscience (164 citations) and Neurology (42 citations). Matei Mancaş has collaborated with scholars based in Belgium, France and Cambodia. Frequent co-authors include Bernard Gosselin, Nicolas Riche, Thierry Dutoit, Matthieu Duvinage, Benoı̂t Macq, Radu-Daniel Vatavu, Benoît Macq, John G. Taylor, Vincent P. Ferrera and Martin Edwards. Their work appears in journals such as Electronics, IEEE Multimedia, Image and Vision Computing, Frontiers in Psychology and Personal and Ubiquitous Computing.
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.