Matej Artač
Impact in
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- Advanced Image and Video Retrieval Techniques
- Face and Expression Recognition
- Advanced Vision and Imaging
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- Software System Performance and Reliability
- IoT and Edge/Fog Computing
Papers in
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- Software System Performance and Reliability 4
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- Cloud Computing and Resource Management 3
- Service-Oriented Architecture and Web Services 2
- Co-authors
- Matjaž Jogan (3 shared papers)Aleš Leonardis (3 shared papers)Damian A. Tamburri (5 shared papers)Michele Guerriero (4 shared papers)Elisabetta Di Nitto (3 shared papers)Pelle Jakovits (1 shared paper)Satish Narayana Srirama (1 shared paper)Giuliano Casale (1 shared paper)
- Journals
- JUCS - Journal of Universal Computer Science (1 paper)Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (4 papers)TU/e Research Portal (1 paper)
- Partner nations
- SloveniaItalyNetherlands
In The Last Decade
Matej Artač
11 papers receiving 310 citations
Peers
Comparison fields: 5 of 53
- Computer Vision and Pattern Recognition 137
- Computer Networks and Communications 125
- Information Systems 119
- Software 20
- Signal Processing 36
Countries citing papers authored by Matej Artač
This map shows the geographic impact of Matej Artač'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 Matej Artač with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matej Artač more than expected).
Fields of papers citing papers by Matej Artač
This network shows the impact of papers produced by Matej Artač. 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 Matej Artač. The network helps show where Matej Artač may publish in the future.
Co-authors
The 17 scholars most cited alongside Matej Artač, 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 | 2003 | 108 | |
| 2 | 2017 | 77 | |
| 3 | 2003 | 54 | |
| 4 | 2019 | 39 | |
| 5 | 2016 | 20 | |
| 6 | 2018 | 18 | |
| 7 | 2011 | 4 | |
| 8 | 2005 | 3 | |
| 9 | 2003 | 3 | |
| 10 | 2017 | 1 | |
| 11 | 2020 | 1 |
About Matej Artač
Matej Artač is a scholar working on Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition, Aerospace Engineering and Management Information Systems, having authored 11 papers that have together received 328 indexed citations. Recurring topics across this work include Software System Performance and Reliability (4 papers), Cloud Computing and Resource Management (3 papers), Robotics and Sensor-Based Localization (3 papers), Advanced Vision and Imaging (3 papers), Image Processing Techniques and Applications (2 papers), Service-Oriented Architecture and Web Services (2 papers), Business Process Modeling and Analysis (2 papers) and Indoor and Outdoor Localization Technologies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (137 citations), Computer Networks and Communications (125 citations), Information Systems (119 citations), Software (20 citations) and Signal Processing (36 citations). Matej Artač has collaborated with scholars based in Slovenia, Italy and Netherlands. Frequent co-authors include Matjaž Jogan, Aleš Leonardis, Damian A. Tamburri, Michele Guerriero, Elisabetta Di Nitto, Pelle Jakovits, Satish Narayana Srirama, Giuliano Casale, Frank Leymann and Alessandra Russo. Their work appears in journals such as JUCS - Journal of Universal Computer Science, Virtual Community of Pathological Anatomy (University of Castilla La Mancha) and TU/e Research Portal.
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.