Hristijan Gjoreski
Hristijan Gjoreski
Ss. Cyril and Methodius University in Skopje, Emteq Labs UK
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Cited by
Cited by
Monitoring stress with a wrist device using context
M Gjoreski, M Luštrek, M Gams, H Gjoreski
Journal of biomedical informatics 73, 159-170, 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
Continuous stress detection using a wrist device: in laboratory and real life
M Gjoreski, H Gjoreski, M Luštrek, M Gams
proceedings of the 2016 ACM international joint conference on pervasive and …, 2016
The university of sussex-huawei locomotion and transportation dataset for multimodal analytics with mobile devices
H Gjoreski, M Ciliberto, L Wang, FJO Morales, S Mekki, S Valentin, ...
IEEE Access 6, 42592-42604, 2018
Enabling reproducible research in sensor-based transportation mode recognition with the Sussex-Huawei dataset
L Wang, H Gjoreski, M Ciliberto, S Mekki, S Valentin, D Roggen
IEEE Access 7, 10870-10891, 2019
How accurately can your wrist device recognize daily activities and detect falls?
M Gjoreski, H Gjoreski, M Luštrek, M Gams
Sensors 16 (6), 800, 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
Summary of the sussex-huawei locomotion-transportation recognition challenge
L Wang, H Gjoreskia, K Murao, T Okita, D Roggen
Proceedings of the 2018 ACM international joint conference and 2018 …, 2018
Comparing deep and classical machine learning methods for human activity recognition using wrist accelerometer
H Gjoreski, J Bizjak, M Gjoreski, M Gams
Proceedings of the IJCAI 2016 Workshop on Deep Learning for Artificial …, 2016
Summary of the Sussex-Huawei locomotion-transportation recognition challenge 2020
L Wang, H Gjoreski, M Ciliberto, P Lago, K Murao, T Okita, D Roggen
Adjunct proceedings of the 2020 ACM international joint conference on …, 2020
Efficient activity recognition and fall detection using accelerometers
S Kozina, H Gjoreski, M Gams, M Luštrek
Evaluating AAL Systems Through Competitive Benchmarking: International …, 2013
Datasets for cognitive load inference using wearable sensors and psychological traits
M Gjoreski, T Kolenik, T Knez, M Luštrek, M Gams, H Gjoreski, V Pejović
Applied Sciences 10 (11), 3843, 2020
Detecting falls with location sensors and accelerometers
M Luštrek, H Gjoreski, S Kozina, B Cvetkovic, V Mirchevska, M Gams
Proceedings of the AAAI Conference on Artificial Intelligence 25 (2), 1662-1667, 2011
Context-based ensemble method for human energy expenditure estimation
H Gjoreski, B Kaluža, M Gams, R Milić, M Luštrek
Applied Soft Computing 37, 960-970, 2015
Three-layer activity recognition combining domain knowledge and meta-classification
S Kozina, H Gjoreski, M Gams, M Luštrek
Journal of Medical and Biological Engineering 33 (4), 406-414, 2013
Competitive live evaluations of activity-recognition systems
H Gjoreski, S Kozina, M Gams, M Lustrek, JA Álvarez-García, JH Hong, ...
IEEE Pervasive Computing 14 (1), 70-77, 2015
Houseec: Day-ahead household electrical energy consumption forecasting using deep learning
I Kiprijanovska, S Stankoski, I Ilievski, S Jovanovski, M Gams, H Gjoreski
Energies 13 (10), 2672, 2020
Activity/posture recognition using wearable sensors placed on different body locations
H Gjoreski, M Gams
Proceedings of (738) Signal and Image Processing and Applications, Crete …, 2011
Detection of gait abnormalities for fall risk assessment using wrist-worn inertial sensors and deep learning
I Kiprijanovska, H Gjoreski, M Gams
Sensors 20 (18), 5373, 2020
Telehealth using ECG sensor and accelerometer
H Gjoreski, A Rashkovska, S Kozina, M Lustrek, M Gams
2014 37th International Convention on Information and Communication …, 2014
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