Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Stefan Kalabakov"'
Autor:
Orhan Konak, Valentin Döring, Tobias Fiedler, Lucas Liebe, Leander Masopust, Kirill Postnov, Franz Sauerwald, Felix Treykorn, Alexander Wischmann, Stefan Kalabakov, Hristijan Gjoreski, Mitja Luštrek, Bert Arnrich
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-12 (2023)
Abstract Accurate and comprehensive nursing documentation is essential to ensure quality patient care. To streamline this process, we present SONAR, a publicly available dataset of nursing activities recorded using inertial sensors in a nursing home.
Externí odkaz:
https://doaj.org/article/75974c2de13e4f8c83138f3fa23526ac
Autor:
Borche Jovanovski, Stefan Kalabakov, Daniel Denkovski, Valentin Rakovic, Bjarne Pfitzner, Orhan Konak, Bert Arnrich, Hristijan Gjoreski
Publikováno v:
Proceedings of the International Conference on Applied Innovations in IT, Vol 11, Iss 1, Pp 119-125 (2023)
The increasing use of Wearable devices opens up the use of a wide range of applications. Using different models, these devices can be of great use in Human Activity Recognition (HAR), where the main goal is to process information obtained from sensor
Externí odkaz:
https://doaj.org/article/6e4a527641644711a0ad26035a72c180
Autor:
Stefan Kalabakov, Borche Jovanovski, Daniel Denkovski, Valentin Rakovic, Bjarne Pfitzner, Orhan Konak, Bert Arnrich, Hristijan Gjoreski
Publikováno v:
IEEE Access, Vol 11, Pp 64442-64457 (2023)
The past decade has seen substantial growth in the prevalence and capabilities of wearable devices. For instance, recent human activity recognition (HAR) research has explored using wearable devices in applications such as remote monitoring of patien
Externí odkaz:
https://doaj.org/article/cf4c5fe29d7f436185045e3d8892305e
Autor:
Stefan Kalabakov, Simon Stankoski, Ivana Kiprijanovska, Andrejaana Andova, Nina Reščič, Vito Janko, Martin Gjoreski, Matjaž Gams, Mitja Luštrek
Publikováno v:
Sensors, Vol 22, Iss 10, p 3613 (2022)
From 2018 to 2021, the Sussex-Huawei Locomotion-Transportation Recognition Challenge presented different scenarios in which participants were tasked with recognizing eight different modes of locomotion and transportation using sensor data from smartp
Externí odkaz:
https://doaj.org/article/0df6b9a029c643edacf4d5f67b639d1c
Publikováno v:
2022 International Balkan Conference on Communications and Networking (BalkanCom).
Autor:
Jože Ravničan, Anže Marinko, Gjorgji Noveski, Stefan Kalabakov, Marko Jovanovič, Samo Gazvoda, Matjaž Gams
Publikováno v:
Informatica. 46
Publikováno v:
Informatica
Human Activity Recognition (HAR) from wearable sensors has gained significant attention in the last few decades, largely because of the potential healthcare benefits. For many years, HAR was done using classical machine learning approaches that requi
Autor:
Ivana Kiprijanovska, John Broulidakis, Simon Stankoski, Hristijan Gjoreski, Charles Nduka, Martin Gjoreski, Stefan Kalabakov
Publikováno v:
Smart Innovation, Systems and Technologies ISBN: 9789811589430
This paper describes the machine learning (ML) method Head-AR, which achieved the highest performance in a competition with 11 other algorithms and won the Emteq Activity Recognition challenge. The goal of the challenge was to recognize eight activit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9ba0cff534d81f4cb8fcf546cb9c63b
https://doi.org/10.1007/978-981-15-8944-7_10
https://doi.org/10.1007/978-981-15-8944-7_10
Autor:
Mitja Luštrek, Stefan Kalabakov, Simon Stankoski, Andrejaana Andova, Vito Janko, Clement Picard, Ivana Kiprijanovska, Martin Gjoreski, Nina Reščič
Publikováno v:
UbiComp/ISWC Adjunct
The SHL recognition challenge 2020 was an open competition in activity recognition where the participants were tasked with recognizing eight different modes of locomotion and transportation with smartphone sensors. The main challenges were that the t
Publikováno v:
Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers
UbiComp/ISWC Adjunct
UbiComp/ISWC Adjunct
Convolution Neural Network (CNN) filters learned on one domain can be used as feature extractors on another similar domain. Transferring filters allow reusing datasets across domains and reducing labelling costs. In this paper, four activity recognit