Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Yunwen Huang"'
Publikováno v:
IEEE Access, Vol 7, Pp 164876-164886 (2019)
The state-of-the-arts in action recognition are suffering from three challenges: (1) How to model spatial transformations of action since it is always geometric variation over time in videos. (2) How to develop the semantic action-aware temporal feat
Externí odkaz:
https://doaj.org/article/cc09f1f9390a4fb78fccdc04205fc2e7
Autor:
Alex Niu, Victor H Ramirez, Bronwyn Gunn, Melyssa Bratton, Sarah Foster, James Robinson, Sree Lanka, Hana Safah, Francisco Socola, Yunwen Huang, Crystal Y Zheng, Ivy V Trinh, Amelie E Murrell, Jeffrey G Shaffer, Elizabeth B Norton, Nakhle S. Saba
Publikováno v:
Blood. 140:8351-8353
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9abffb38dd1779b1fef30cec9540c2e0
https://doi.org/10.1182/blood-2022-165019
https://doi.org/10.1182/blood-2022-165019
Publikováno v:
Medical physicsREFERENCES. 49(10)
Radiotherapy to tumors in the abdomen is challenging because of the significant organ movement and tissue deformation caused by respiration.A motion management strategy that integrated ultrasound (US) imaging with abdominal compression was developed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b65bd14b1b786d4f166b75cd3b6dd962
https://pubmed.ncbi.nlm.nih.gov/35950934
https://pubmed.ncbi.nlm.nih.gov/35950934
Publikováno v:
Biophotonics Congress: Biomedical Optics 2022 (Translational, Microscopy, OCT, OTS, BRAIN).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12d62e98389c766e208e48c963363f17
https://doi.org/10.1364/ots.2022.otu2d.6
https://doi.org/10.1364/ots.2022.otu2d.6
Autor:
Fei Wang, Xiaohan Gao, Xingqun Zhou, Huan Qi, Yunwen Huang, Xiaojun Sun, Xiao Meng, Yucheng Long
Publikováno v:
2018 IEEE 8th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER).
On the basis of demonstration experience gained through demonstration learning, this paper proposes an interactive robot learning system, which uses wearable sensors that can detect surface electromyography signals (sEMG)and inertial information. Ges
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4df050f14b665c8d2abe5c85f2efa3cb
https://doi.org/10.1109/cyber.2018.8688213
https://doi.org/10.1109/cyber.2018.8688213