Mitja Luštrek
Impact in
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- Context-Aware Activity Recognition Systems
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- Emotion and Mood Recognition
Papers in
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- Context-Aware Activity Recognition Systems 44
- Human Pose and Action Recognition 9
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- Anomaly Detection Techniques and Applications 15
- Artificial Intelligence in Games 9
- Co-authors
- Matjaž Gams (53 shared papers)Hristijan Gjoreski (24 shared papers)Martin Gjoreski (22 shared papers)Gašper Slapničar (16 shared papers)Boštjan Kaluža (10 shared papers)Božidara Cvetković (20 shared papers)Vito Janko (20 shared papers)Anton Gradišek (16 shared papers)
In The Last Decade
Mitja Luštrek
129 papers receiving 2.6k citations
Mitja Luštrek's Hit Papers
Peers
Comparison fields: 5 of 158
- Computer Vision and Pattern Recognition 848
- Experimental and Cognitive Psychology 388
- Cardiology and Cardiovascular Medicine 548
- Health Information Management 92
- Biomedical Engineering 898
Countries citing papers authored by Mitja Luštrek
This map shows the geographic impact of Mitja Luštrek'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 Mitja Luštrek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mitja Luštrek more than expected).
Fields of papers citing papers by Mitja Luštrek
This network shows the impact of papers produced by Mitja Luštrek. 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 Mitja Luštrek. The network helps show where Mitja Luštrek may publish in the future.
Co-authors
The 25 scholars most cited alongside Mitja Luštrek, 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 136 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Blood Pressure Estimation from Photoplethysmogram Using a Spectro-Temporal Deep Neural Network Hit paper breakdown → | 2019 | 257 |
| 2 | 2017 | 240 | |
| 3 | 2016 | 155 | |
| 4 | 2011 | 154 | |
| 5 | Fall Detection and Activity Recognition with Machine Learning | 2009 | 147 |
| 6 | 2016 | 82 | |
| 7 | 2020 | 67 | |
| 8 | 2020 | 66 | |
| 9 | 2021 | 65 | |
| 10 | 2020 | 64 | |
| 11 | 2017 | 63 | |
| 12 | Continuous Blood Pressure Estimation from PPG Signal | 2018 | 49 |
| 13 | 2016 | 48 | |
| 14 | 2016 | 43 | |
| 15 | 2015 | 41 | |
| 16 | 2020 | 40 | |
| 17 | 2018 | 34 | |
| 18 | 2022 | 31 | |
| 19 | 2012 | 30 | |
| 20 | 2011 | 29 |
About Mitja Luštrek
Mitja Luštrek is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering, Surgery and Cardiology and Cardiovascular Medicine, having authored 136 papers that have together received 2.7k indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (44 papers), Non-Invasive Vital Sign Monitoring (16 papers), Anomaly Detection Techniques and Applications (15 papers), Gait Recognition and Analysis (10 papers), Physical Activity and Health (9 papers), EEG and Brain-Computer Interfaces (9 papers), Artificial Intelligence in Games (9 papers) and Human Pose and Action Recognition (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (848 citations), Experimental and Cognitive Psychology (388 citations), Cardiology and Cardiovascular Medicine (548 citations), Health Information Management (92 citations) and Biomedical Engineering (898 citations). Mitja Luštrek has collaborated with scholars based in Slovenia, Germany and Belgium. Frequent co-authors include Matjaž Gams, Hristijan Gjoreski, Martin Gjoreski, Gašper Slapničar, Boštjan Kaluža, Božidara Cvetković, Vito Janko, Anton Gradišek, Erik Dovgan and Veljko Pejović. Their work appears in journals such as Sensors, PLoS ONE, International Journal of Environmental Research and Public Health, Expert Systems with Applications and IEEE Pervasive 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.