Zobrazeno 1 - 10
of 4 303
pro vyhledávání: '"Bo, Du"'
The task of single-source domain generalization (SDG) in medical image segmentation is crucial due to frequent domain shifts in clinical image datasets. To address the challenge of poor generalization across different domains, we introduce a Plug-and
Externí odkaz:
http://arxiv.org/abs/2403.11689
CNNs and Transformers have their own advantages and both have been widely used for dense prediction in multi-task learning (MTL). Most of the current studies on MTL solely rely on CNN or Transformer. In this work, we present a novel MTL model by comb
Externí odkaz:
http://arxiv.org/abs/2308.05721
Autor:
Chun-Hong Du, Rong Xiang, Shuang-Shuang Bie, Xing Yang, Ji-Hu Yang, Ming-Guo Yao, Yun Zhang, Zhi-Hai He, Zong-Ti Shao, Chun-Feng Luo, En-Nian Pu, Yu-Qiong Li, Fan Wang, Zhi Luo, Chao-Bo Du, Jie Zhao, Miao Li, Wu-Chun Cao, Yi Sun, Jia-Fu Jiang
Publikováno v:
Infectious Diseases of Poverty, Vol 13, Iss 1, Pp 1-16 (2024)
Abstract Background Rickettsia and related diseases have been identified as significant global public health threats. This study involved comprehensive field and systematic investigations of various rickettsial organisms in Yunnan Province. Methods B
Externí odkaz:
https://doaj.org/article/cec9878c647044b6874ff3dc4f12da1a
Publikováno v:
International Journal of Transportation Science and Technology, Vol 14, Iss , Pp 137-155 (2024)
The significance of intelligent transportation systems and artificial intelligence in road transportation networks has made the prediction of traffic flow a subject of discussion among transportation engineers, urban planners, and researchers in the
Externí odkaz:
https://doaj.org/article/82ee4edd7a2a4bd5b2abdaa7b1a28e4d
Autor:
Tianyang Mao, Xin Zhao, Kangyi Jiang, Jie Yang, Qingyun Xie, Jinqiang Fu, Bo Du, Zehua Lei, Fengwei Gao
Publikováno v:
BMC Public Health, Vol 24, Iss 1, Pp 1-8 (2024)
Abstract Background Acute pancreatitis (AP) is a common acute digestive system disorder, with patients often turning to TikTok for AP-related information. However, the platform’s video quality on AP has not been thoroughly investigated. Objective T
Externí odkaz:
https://doaj.org/article/6886a4bae7664e6a91862e4d086b0673
Publikováno v:
Journal of Transportation Engineering, Part A: Systems. 144
Autor:
Xiaoling Wang, He Li, Hongmei Zheng, Gongpeng Sun, Wenyu Wang, Zuohuizi Yi, A’min Xu, Lu He, Haiyan Wang, Wei Jia, Zhiqing Li, Chang Li, Mang Ye, Bo Du, Changzheng Chen
Publikováno v:
Ophthalmology and Therapy, Vol 13, Iss 5, Pp 1125-1144 (2024)
Abstract Introduction Inaccurate, untimely diagnoses of fundus diseases leads to vision-threatening complications and even blindness. We built a deep learning platform (DLP) for automatic detection of 30 fundus diseases using ultra-widefield fluoresc
Externí odkaz:
https://doaj.org/article/a000206bca434540beca9f51dac0635b
Publikováno v:
AIMS Mathematics, Vol 9, Iss 3, Pp 6321-6335 (2024)
This paper aims to study a class of enterprise cluster models with feedback controls and time-varying delays on time scales. Based on periodic time scales theory and the fixed point theorem of strict-set-contraction, some new sufficient conditions fo
Externí odkaz:
https://doaj.org/article/ca3042d67bb44c23ad860ccd0b9355e4
Autor:
Di Wang, Jing Zhang, Minqiang Xu, Lin Liu, Dongsheng Wang, Erzhong Gao, Chengxi Han, Haonan Guo, Bo Du, Dacheng Tao, Liangpei Zhang
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11632-11654 (2024)
Foundation models have reshaped the landscape of remote sensing (RS) by enhancing various image interpretation tasks. Pretraining is an active research topic, encompassing supervised and self-supervised learning methods to initialize model weights ef
Externí odkaz:
https://doaj.org/article/f1ebc4a04ca145599622a4482d62ea54
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 1523-1534 (2024)
Hyperspectral change detection (CD) aims to obtain the change information of objects in the multitemporal hyperspectral images (HSIs). Recently, with the advantages in fully extracting the image features of irregular areas, the graph convolutional ne
Externí odkaz:
https://doaj.org/article/d87083d30df349abb14ef5d126014b4f