Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Xingxing Liao"'
Autor:
Zhiqing Tang, Wenlong Su, Tianhao Liu, Haitao Lu, Ying Liu, Hui Li, Kaiyue Han, Md. Moneruzzaman, Junzi Long, Xingxing Liao, Xiaonian Zhang, Lei Shan, Hao Zhang
Publikováno v:
BMC Neurology, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background Accurately predicting the walking independence of stroke patients is important. Our objective was to determine and compare the performance of logistic regression (LR) and three machine learning models (eXtreme Gradient Boosting (X
Externí odkaz:
https://doaj.org/article/cb5b4d2b4d764ab8a58ffec2567c36e2
Autor:
Junzi Long, Hui Li, Ying Liu, Xingxing Liao, Zhiqing Tang, Kaiyue Han, Jiarou Chen, Hao Zhang
Publikováno v:
Frontiers in Psychiatry, Vol 15 (2024)
The hippocampus is one of the brain areas affected by autism spectrum disorder (ASD). Individuals with ASD typically have impairments in hippocampus-dependent learning, memory, language ability, emotional regulation, and cognitive map creation. Howev
Externí odkaz:
https://doaj.org/article/5c0cb0a55d09468da86f4a0639158139
Publikováno v:
Electronics Letters, Vol 59, Iss 20, Pp n/a-n/a (2023)
Abstract This letter proposes a data‐driven method to simulate random sea clutter amplitude sequence with distribution and correlation characteristics directly inherited from the measured clutter. First, a generation model is developed to simulate
Externí odkaz:
https://doaj.org/article/75edfbe61abf45aa9a44f381c36ed254
Publikováno v:
Leida xuebao, Vol 10, Iss 6, Pp 874-884 (2021)
Low-oversampled staggered synthetic aperture radar can achieve continuously observed high-resolution and wide-swath imaging by utilizing the variable pulse repetition interval to distribute blind ranges. Moreover, adopting a low oversampling ratio ca
Externí odkaz:
https://doaj.org/article/ddc2def854f04644a8c869503e673e7f
Publikováno v:
IEEE Access, Vol 8, Pp 40367-40377 (2020)
The diversity and the space-variance of the spectrum-aliasing effects in SAR bring challenges to the available model-driven restoration methods. In this paper, a hybrid data-driven and model-driven deep learning scheme is innovatively proposed to dea
Externí odkaz:
https://doaj.org/article/b2f2b8537a244e5d864a1d2fcf9ede13
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-23
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f0ea9d762010f8020ebad5208406c39
https://doi.org/10.1109/tgrs.2022.3205737
https://doi.org/10.1109/tgrs.2022.3205737
This paper focuses on processing low oversampling echo data of staggered synthetic aperture radar (SAR). In staggered mode, the non-uniformly sampling and irregular loss of echo data cause azimuth ambiguity which severely degrades the imaging quality
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70268a6fd87740d70b0a29c4f317e5be
Publikováno v:
IGARSS
This paper focuses on processing low oversampling echo data of staggered synthetic aperture radar (SAR). In staggered mode, the non-uniformly sampling and echo data loss cause severe azimuth ambiguity. To solve this problem, we propose a method combi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f27ac5705ccc3f2fc63db8b19d825b4
https://doi.org/10.1109/igarss39084.2020.9324092
https://doi.org/10.1109/igarss39084.2020.9324092