Zobrazeno 1 - 10
of 256
pro vyhledávání: '"YONGHUAI LIU"'
Autor:
Jinkui Hao, William R. Kwapong, Ting Shen, Huazhu Fu, Yanwu Xu, Qinkang Lu, Shouyue Liu, Jiong Zhang, Yonghuai Liu, Yifan Zhao, Yalin Zheng, Alejandro F. Frangi, Shuting Zhang, Hong Qi, Yitian Zhao
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-15 (2024)
Abstract Alzheimer’s disease (AD) is a global healthcare challenge lacking a simple and affordable detection method. We propose a novel deep learning framework, Eye-AD, to detect Early-onset Alzheimer’s Disease (EOAD) and Mild Cognitive Impairmen
Externí odkaz:
https://doaj.org/article/115bca79ccd9460a9957d99159c027dd
Publikováno v:
Sensors, Vol 23, Iss 20, p 8649 (2023)
With the advent of autonomous vehicles, sensors and algorithm testing have become crucial parts of the autonomous vehicle development cycle. Having access to real-world sensors and vehicles is a dream for researchers and small-scale original equipmen
Externí odkaz:
https://doaj.org/article/f692893b66834e558a0d814d1f5c626b
Autor:
Morteza Ghahremani, Kevin Williams, Fiona M. K. Corke, Bernard Tiddeman, Yonghuai Liu, John H. Doonan
Publikováno v:
Frontiers in Plant Science, Vol 12 (2021)
The 3D analysis of plants has become increasingly effective in modeling the relative structure of organs and other traits of interest. In this paper, we introduce a novel pattern-based deep neural network, Pattern-Net, for segmentation of point cloud
Externí odkaz:
https://doaj.org/article/5cdf0ae24482420ba8f19d808e24338e
Publikováno v:
Applied Sciences, Vol 10, Iss 22, p 8248 (2020)
A typical pulsed thermography procedure results in a sequence of infrared images that reflects the evolution of temperature over time. Many features of defects, such as shape, position, and size, are derived from single image by image processing. Hen
Externí odkaz:
https://doaj.org/article/105e428764bd49ea8b9d5aefaeac117c
Publikováno v:
PLoS ONE, Vol 10, Iss 4, p e0127486 (2015)
Externí odkaz:
https://doaj.org/article/bca7277a1c5b42a6a066a8d844428eb8
Publikováno v:
PLoS ONE, Vol 10, Iss 4, p e0122332 (2015)
Our application concerns the automated detection of vessels in retinal images to improve understanding of the disease mechanism, diagnosis and treatment of retinal and a number of systemic diseases. We propose a new framework for segmenting retinal v
Externí odkaz:
https://doaj.org/article/28270e0bfd1b41c29e45873f8e0b43d1
Autor:
Jianyang Xie, Quanyong Yi, Yufei Wu, Yalin Zheng, Yonghuai Liu, Macerollo, Antonella, Huazhu Fu, Yanwu Xu, Jiong Zhang, Behera, Ardhendu, Chenlei Fan, Frangi, Alejandro F., Jiang Liu, Qinkang Lu, Hong Qi, Yitian Zhao
Publikováno v:
British Journal of Ophthalmology; Mar2024, Vol. 108 Issue 3, p432-439, 17p
Publikováno v:
IEEE Transactions on Affective Computing. 14:549-562
Affect is often expressed via non-verbal body language such as actions/gestures, which are vital indicators for human behaviors. Recent studies on recognition of fine-grained actions/gestures in monocular images have mainly focused on modeling spatia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0a10e0fa13aa9f42a5f5ba3fdc4253e
https://doi.org/10.1109/taffc.2020.3031841
https://doi.org/10.1109/taffc.2020.3031841
Publikováno v:
International Journal of Computer Vision. 130:1210-1227
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::11a602fc96079b672c76242eddf29786
https://doi.org/10.1007/s11263-022-01592-x
https://doi.org/10.1007/s11263-022-01592-x
Autor:
Hong Qi, Jiong Zhang, Yufei Wu, Yuhui Ma, Yonghuai Liu, Yan Hu, Huazhu Fu, Yitian Zhao, Jiang Liu, Jun Cheng
Publikováno v:
IEEE Transactions on Medical Imaging. 40:3955-3967
The development of medical imaging techniques has greatly supported clinical decision making. However, poor imaging quality, such as non-uniform illumination or imbalanced intensity, brings challenges for automated screening, analysis and diagnosis o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3dc27752c6a009cef616c53eb45b79cf
https://doi.org/10.1109/tmi.2021.3101937
https://doi.org/10.1109/tmi.2021.3101937