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pro vyhledávání: '"Xu, Qisen"'
Autor:
Mao, Xiaowei, Lin, Yan, Guo, Shengnan, Chen, Yubin, Xian, Xingyu, Wen, Haomin, Xu, Qisen, Lin, Youfang, Wan, Huaiyu
Uncertainty quantification in travel time estimation (TTE) aims to estimate the confidence interval for travel time, given the origin (O), destination (D), and departure time (T). Accurately quantifying this uncertainty requires generating the most l
Externí odkaz:
http://arxiv.org/abs/2408.12809
Autor:
Zhou, Zeyu, Lin, Yan, Wen, Haomin, Xu, Qisen, Guo, Shengnan, Hu, Jilin, Lin, Youfang, Wan, Huaiyu
Spatio-temporal trajectories are crucial in various data mining tasks. It is important to develop a versatile trajectory learning method that performs different tasks with high accuracy. This involves effectively extracting two core aspects of inform
Externí odkaz:
http://arxiv.org/abs/2405.12459
Publikováno v:
IEEE Transactions on Medical Imaging, vol. 40, no. 10, pp. 2563-2574, Oct. 2021
Interactive segmentation has recently been explored to effectively and efficiently harvest high-quality segmentation masks by iteratively incorporating user hints. While iterative in nature, most existing interactive segmentation methods tend to igno
Externí odkaz:
http://arxiv.org/abs/2303.10692
Autor:
Li, Wenhao, Xu, Qisen, Shen, Chuyun, Hu, Bin, Zhu, Fengping, Li, Yuxin, Jin, Bo, Wang, Xiangfeng
Medical image segmentation is one of the fundamental problems for artificial intelligence-based clinical decision systems. Current automatic medical image segmentation methods are often failed to meet clinical requirements. As such, a series of inter
Externí odkaz:
http://arxiv.org/abs/2111.07716
Autor:
Liao, Xuan, Li, Wenhao, Xu, Qisen, Wang, Xiangfeng, Jin, Bo, Zhang, Xiaoyun, Zhang, Ya, Wang, Yanfeng
Existing automatic 3D image segmentation methods usually fail to meet the clinic use. Many studies have explored an interactive strategy to improve the image segmentation performance by iteratively incorporating user hints. However, the dynamic proce
Externí odkaz:
http://arxiv.org/abs/1911.10334
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Akademický článek
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