Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Qingfeng Dai"'
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 750-758 (2024)
The conventional surface electromyography (sEMG)-based gesture recognition systems exhibit impressive performance in controlled laboratory settings. As most systems are trained in a closed-set setting, the systems’s performance may see significant
Externí odkaz:
https://doaj.org/article/cbd068913d444d699b46a584680c004f
Publikováno v:
Bioengineering, Vol 10, Iss 9, p 1101 (2023)
To enhance the performance of surface electromyography (sEMG)-based gesture recognition, we propose a novel network-agnostic two-stage training scheme, called sEMGPoseMIM, that produces trial-invariant representations to be aligned with corresponding
Externí odkaz:
https://doaj.org/article/dfb5b428854e4a7e9a3956829ca7ccd7
Autor:
QINGFENG DAI, YONGKANG WONG, GUOFEI SUN, YANWEI WANG, ZHOU ZHOU, KANKANHALLI, MOHAN S., XIANGDONG LI, WEIDONG GENG
Publikováno v:
ACM Transactions on Multimedia Computing, Communications & Applications; Feb2024, Vol. 20 Issue 2, p1-18, 18p
Publikováno v:
IEEE Access, Vol 7, Pp 104108-104120 (2019)
To improve the accuracy of surface electromyography (sEMG)-based gesture recognition, we present a novel hybrid approach that combines real sEMG signals with corresponding virtual hand poses. The virtual hand poses are generated by means of a propose
Externí odkaz:
https://doaj.org/article/162171b3c24d4261a5b223ec432be4c3
Publikováno v:
Mitochondrial DNA. Part B. Resources, Vol 6, Iss 3, Pp 794-795 (2021)
The mitochondrial genome of the Reticulitermes ovatilabrum is 15,913 bp in length and encodes 37 genes including 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNA), 2 ribosomal RNA genes (rRNA), and a non-coding control region (D-loop). The
Externí odkaz:
https://doaj.org/article/e5fe2dfcfb254460966ee596ce1b29c7
Autor:
Qingfeng Dai, Yongkang Wong, Guofei Sun, Yanwei Wang, Zhou Zhou, Mohan S. Kankanhalli, Xiangdong Li, Weidong Geng
Publikováno v:
ACM Transactions on Multimedia Computing, Communications, and Applications.
Biometric signal based human-computer interface (HCI) has attracted increasing attention due to its wide application in healthcare, entertainment, neurocomputing, and so on. In recent years, deep learning based approaches have made great progress on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d493787d06dd553ddb4234ab8990878
https://doi.org/10.1145/3583885
https://doi.org/10.1145/3583885
Publikováno v:
Journal of Asia-Pacific Entomology. 24:421-428
Pseudocapritermes Kemner is a termite group that constructs subterranean gallery systems in topsoil. This genus is distributed in the Oriental region and contains 18 species. Dependence on the morphological measurements of soldiers makes the taxonomy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1bdbdab902204a7de813a80caadc7374
https://doi.org/10.1016/j.aspen.2021.01.004
https://doi.org/10.1016/j.aspen.2021.01.004
Publikováno v:
The 2021 9th International Conference on Computer and Communications Management.
The recent progress in sEMG-based hand gesture detection has developed a set of predefined hand gestures for interaction. However, customized hand gestures are less concerned due to the lack of supporting tools for training alternative hand gestures.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9a0cd12879ffc519c135b1985bed06f
https://doi.org/10.1145/3479162.3479170
https://doi.org/10.1145/3479162.3479170
Publikováno v:
IEEE Transactions on Biomedical Engineering. 66:2964-2973
Gesture recognition using sparse multichannel surface electromyography (sEMG) is a challenging problem, and the solutions are far from optimal from the point of view of muscle-computer interface. In this paper, we address this problem from the contex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cbe6d24cd1fdac0763281f904ce7e782
https://doi.org/10.1109/tbme.2019.2899222
https://doi.org/10.1109/tbme.2019.2899222