| Monitoring stress with a wrist device using context M Gjoreski, M Luątrek, M Gams, H Gjoreski Journal of biomedical informatics 73, 159-170, 2017 | 318 | 2017 |
| Accelerometer placement for posture recognition and fall detection H Gjoreski, M Lustrek, M Gams 2011 Seventh International Conference on Intelligent Environments, 47-54, 2011 | 292 | 2011 |
| Blood pressure estimation from photoplethysmogram using a spectro-temporal deep neural network G Slapničar, N Mlakar, M Luątrek Sensors 19 (15), 3420, 2019 | 287 | 2019 |
| Continuous stress detection using a wrist device: in laboratory and real life M Gjoreski, H Gjoreski, M Luątrek, M Gams proceedings of the 2016 ACM international joint conference on pervasive and …, 2016 | 236 | 2016 |
| An agent-based approach to care in independent living B Kaluľa, V Mirchevska, E Dovgan, M Luątrek, M Gams Ambient Intelligence: First International Joint Conference, AmI 2010, Malaga …, 2010 | 201 | 2010 |
| Fall detection and activity recognition with machine learning M Luątrek, B Kaluľa Informatica 33 (2), 2009 | 175 | 2009 |
| Fall detection and activity recognition with machine learning M Lustrek Informatica 33 (2), 205-212, 2009 | 150 | 2009 |
| How accurately can your wrist device recognize daily activities and detect falls? M Gjoreski, H Gjoreski, M Luątrek, M Gams Sensors 16 (6), 800, 2016 | 143 | 2016 |
| Automatic detection of perceived stress in campus students using smartphones M Gjoreski, H Gjoreski, M Lutrek, M Gams 2015 international conference on intelligent environments, 132-135, 2015 | 97 | 2015 |
| Classical and deep learning methods for recognizing human activities and modes of transportation with smartphone sensors M Gjoreski, V Janko, G Slapničar, M Mlakar, N Reąčič, J Bizjak, V Drobnič, ... Information Fusion 62, 47-62, 2020 | 90 | 2020 |
| Real-time activity monitoring with a wristband and a smartphone B Cvetković, R Szeklicki, V Janko, P Lutomski, M Luątrek Information Fusion 43, 77-93, 2018 | 82 | 2018 |
| What makes classification trees comprehensible? R Piltaver, M Luątrek, M Gams, S Martinčić-Ipąić Expert Systems with Applications 62, 333-346, 2016 | 79* | 2016 |
| Machine learning prediction models for chronic kidney disease using national health insurance claim data in Taiwan S Krishnamurthy, K Ks, E Dovgan, M Luątrek, B Gradiąek Piletič, ... Healthcare 9 (5), 546, 2021 | 74 | 2021 |
| Efficient activity recognition and fall detection using accelerometers S Kozina, H Gjoreski, M Gams, M Luątrek Evaluating AAL Systems Through Competitive Benchmarking: International …, 2013 | 72 | 2013 |
| Continuous blood pressure estimation from PPG signal G Slapničar, M Luątrek, M Marinko Informatica 42 (1), 2018 | 68 | 2018 |
| Datasets for cognitive load inference using wearable sensors and psychological traits M Gjoreski, T Kolenik, T Knez, M Luątrek, M Gams, H Gjoreski, V Pejović Applied Sciences 10 (11), 3843, 2020 | 67 | 2020 |
| Detecting falls with location sensors and accelerometers M Luątrek, H Gjoreski, S Kozina, B Cvetkovic, V Mirchevska, M Gams Proceedings of the AAAI Conference on Artificial Intelligence 25 (2), 1662-1667, 2011 | 67 | 2011 |
| Machine learning and end-to-end deep learning for monitoring driver distractions from physiological and visual signals M Gjoreski, M® Gams, M Luątrek, P Genc, JU Garbas, T Hassan IEEE access 8, 70590-70603, 2020 | 64 | 2020 |
| Context-based ensemble method for human energy expenditure estimation H Gjoreski, B Kaluľa, M Gams, R Milić, M Luątrek Applied Soft Computing 37, 960-970, 2015 | 64 | 2015 |
| Dynamic control in real-time heuristic search V Bulitko, M Lustrek, J Schaeffer, Y Bjornsson, S Sigmundarson Journal of Artificial Intelligence Research 32, 419-452, 2008 | 59 | 2008 |
Matjaz GamsJozef Stefan InstituteE-mail megerősítve itt: ijs.si
