Zobrazeno 1 - 10
of 1 816
pro vyhledávání: '"LIU Ziyu"'
Publikováno v:
罕见病研究, Vol 3, Iss 3, Pp 405-410 (2024)
The prevention and treatment of rare diseases is an important public health issue in China. Rare diseases are characterized by diverse types, complex conditions, and heavy burdened to patients, leading to a series of issues in the urgent demand in pr
Externí odkaz:
https://doaj.org/article/2f8d20b8bd5649e48231169554aaf60a
Publikováno v:
Frontiers in Public Health, Vol 12 (2024)
IntroductionPilots’ safety attitude is crucial for aviation safety. Current research shows a correlation between perceived stress and safety attitude, yet the mechanism underlying this association remains unclear. Against the backdrop of heightened
Externí odkaz:
https://doaj.org/article/917afadbd4bc43038c93548e14c55c10
Autor:
Liu Ziyu
Publikováno v:
SHS Web of Conferences, Vol 187, p 04005 (2024)
Hoque and Noon claim that many workplace equal opportunities policies in the UK are merely ‘empty shells’. This article will discuss this claim and consider the extent to which radical equal opportunities policies may address these shortcomings.
Externí odkaz:
https://doaj.org/article/4fc5328cd6634cf998c815b57636042b
Autor:
Liu Ziyu, Zheng Yutong
Publikováno v:
SHS Web of Conferences, Vol 181, p 03012 (2024)
In recent years, the new energy vehicle (NEV) industry has rapidly grown and become a vital part of the automotive sector. Supply chain finance plays a critical role in the NEV industry as it affects the operation and development of the entire indust
Externí odkaz:
https://doaj.org/article/3ade237e0a6444ff8e622f7ce751663d
Publikováno v:
Xiehe Yixue Zazhi, Vol 13, Iss 4, Pp 620-625 (2022)
Objective To evaluate the clinical application value of the compression and storage algorithm of histopathological images based on matrix computing, and to seek the best image compression ratio. Methods Two classical matrix algorithms, principal comp
Externí odkaz:
https://doaj.org/article/c1ce34a50f464bc4bdca89af57e6cc6c
Autor:
Liu, Ziyu, Zang, Yuhang, Dong, Xiaoyi, Zhang, Pan, Cao, Yuhang, Duan, Haodong, He, Conghui, Xiong, Yuanjun, Lin, Dahua, Wang, Jiaqi
Visual preference alignment involves training Large Vision-Language Models (LVLMs) to predict human preferences between visual inputs. This is typically achieved by using labeled datasets of chosen/rejected pairs and employing optimization algorithms
Externí odkaz:
http://arxiv.org/abs/2410.17637
We study the large deviation principle (LDP) for locally damped nonlinear wave equations perturbed by a bounded noise. When the noise is sufficiently non-degenerate, we establish the LDP for empirical distributions with lower bound of a local type. T
Externí odkaz:
http://arxiv.org/abs/2409.11717
We establish a new criterion for exponential mixing of random dynamical systems. Our criterion is applicable to a wide range of systems, including in particular dispersive equations. Its verification is in nature related to several topics, i.e., asym
Externí odkaz:
http://arxiv.org/abs/2407.15058
ESP-MedSAM: Efficient Self-Prompting SAM for Universal Domain-Generalized Medical Image Segmentation
Autor:
Xu, Qing, Li, Jiaxuan, He, Xiangjian, Liu, Ziyu, Chen, Zhen, Duan, Wenting, Li, Chenxin, He, Maggie M., Tesema, Fiseha B., Cheah, Wooi P., Wang, Yi, Qu, Rong, Garibaldi, Jonathan M.
The universality of deep neural networks across different modalities and their generalization capabilities to unseen domains play an essential role in medical image segmentation. The recent Segment Anything Model (SAM) has demonstrated its potential
Externí odkaz:
http://arxiv.org/abs/2407.14153
Self-supervised contrastive learning has become a key technique in deep learning, particularly in time series analysis, due to its ability to learn meaningful representations without explicit supervision. Augmentation is a critical component in contr
Externí odkaz:
http://arxiv.org/abs/2407.09336