Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Seok-Lyong Lee"'
Publikováno v:
Sensors, Vol 22, Iss 22, p 8898 (2022)
Industries need a mechanism to monitor the workers’ safety and to prevent Work-related Musculoskeletal Disorders (WMSDs). The development of ergonomics assessment tools helps the industry evaluate workplace design and worker posture. Many studies p
Externí odkaz:
https://doaj.org/article/5c622ee362ee4264bc22501c6072007a
Publikováno v:
Future Generation Computer Systems. 133:114-123
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3063b69b2291188e550bf6831425d2d2
https://doi.org/10.1016/j.future.2022.03.006
https://doi.org/10.1016/j.future.2022.03.006
Publikováno v:
Neural Processing Letters.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61269148cc5254c916230a9e837f45e9
https://doi.org/10.1007/s11063-023-11203-6
https://doi.org/10.1007/s11063-023-11203-6
Autor:
Sunder Ali Khowaja, Seok-Lyong Lee
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing. 13:3729-3746
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9cdd6764bf29816b36f883580d0e8056
https://doi.org/10.1007/s12652-022-03848-3
https://doi.org/10.1007/s12652-022-03848-3
Autor:
Ericka Pamela Bermudez Pillado, Tori Bukit, Sean Yonathan Tanjung, Hyun-Woo Lim, Ignatius Iwan, Bernardo Nugroho Yahya, Seok-Lyong Lee
Publikováno v:
Intelligent Human Computer Interaction ISBN: 9783031271984
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81872823adbd8306027d23d842fdebbf
https://doi.org/10.1007/978-3-031-27199-1_42
https://doi.org/10.1007/978-3-031-27199-1_42
Publikováno v:
Pattern Analysis and Applications. 24:1501-1511
Common approaches in the cross-domain sensor-based human activity recognition are based on the homogeneous domain adaptation which relies on the assumption that the training and testing data are of homogeneous feature space. In reality, such an assum
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a82294fd370cc3bb87517ebf03c4c4ba
https://doi.org/10.1007/s10044-021-00995-9
https://doi.org/10.1007/s10044-021-00995-9
Publikováno v:
The Journal of Korean Institute of Information Technology. 19:11-21
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4db3c8c6030be08babb8708b67db6a5b
https://doi.org/10.14801/jkiit.2021.19.1.11
https://doi.org/10.14801/jkiit.2021.19.1.11
Publikováno v:
Human-Centric Computing and Information Sciences, Vol 10, Iss 1, Pp 1-35 (2020)
The existing action recognition systems mainly focus on generalized methods to categorize human actions. However, the generalized systems cannot attain the same level of recognition performance for new users mainly due to the high variance in terms o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a38eb27f984ee9c454146e536ff80cd4
http://link.springer.com/article/10.1186/s13673-020-00240-y
http://link.springer.com/article/10.1186/s13673-020-00240-y
Publikováno v:
Information Systems Frontiers. 23:71-80
The sensor-based human activity recognition (HAR) using machine learning requires a sufficiently large amount of annotated data to realize an accurate classification model. This requirement stimulates the advancement of the transfer learning research
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a177ed678f160797a96ec151f0aa27f
https://doi.org/10.1007/s10796-020-09992-5
https://doi.org/10.1007/s10796-020-09992-5
Publikováno v:
COMPSAC
Due to the rapid development of sensor technology, wearable sensors have been widely applied in various real-life human applications and improved the mass adoption of smart environments. This recent technology offers a pioneering opportunity to recog
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1229762107ed000349a9d4d8eef67d8d
https://doi.org/10.1109/compsac51774.2021.00093
https://doi.org/10.1109/compsac51774.2021.00093