Zobrazeno 1 - 10
of 492
pro vyhledávání: '"Tai-Xue An"'
Autor:
Yue-Ting Tang, Yi-Yao Huang, Jing-Huan Li, Si-Hua Qin, Yong Xu, Tai-Xue An, Chun-Chen Liu, Qian Wang, Lei Zheng
Publikováno v:
BMC Genomics, Vol 24, Iss 1, Pp 1-2 (2023)
Externí odkaz:
https://doaj.org/article/385d776f4af64eaa9ed527bc74ff7b58
Shape compactness is a key geometrical property to describe interesting regions in many image segmentation tasks. In this paper, we propose two novel algorithms to solve the introduced image segmentation problem that incorporates a shape-compactness
Externí odkaz:
http://arxiv.org/abs/2406.19400
Autor:
Yue-Ting Tang, Yi-Yao Huang, Jing-Huan Li, Si-Hua Qin, Yong Xu, Tai-Xue An, Chun-Chen Liu, Qian Wang, Lei Zheng
Publikováno v:
BMC Genomics, Vol 19, Iss 1, Pp 1-14 (2018)
Abstract Background Epithelial–mesenchymal transition (EMT) is regarded as a critical event during tumor metastasis. Recent studies have revealed changes and the contributions of proteins in/on exosomes during EMT. Besides proteins, microRNA (miRNA
Externí odkaz:
https://doaj.org/article/fdb319cf01db4491ac0bafc6a05a437e
BP-DeepONet: A new method for cuffless blood pressure estimation using the physcis-informed DeepONet
Cardiovascular diseases (CVDs) are the leading cause of death worldwide, with blood pressure serving as a crucial indicator. Arterial blood pressure (ABP) waveforms provide continuous pressure measurements throughout the cardiac cycle and offer valua
Externí odkaz:
http://arxiv.org/abs/2402.18886
In this study, our goal is to integrate classical mathematical models with deep neural networks by introducing two novel deep neural network models for image segmentation known as Double-well Nets. Drawing inspirations from the Potts model, our model
Externí odkaz:
http://arxiv.org/abs/2401.00456
Investigating blood flow in the cardiovascular system is crucial for assessing cardiovascular health. Computational approaches offer some non-invasive alternatives to measure blood flow dynamics. Numerical simulations based on traditional methods suc
Externí odkaz:
http://arxiv.org/abs/2312.05601
The Euler Elastica (EE) model with surface curvature can generate artifact-free results compared with the traditional total variation regularization model in image processing. However, strong nonlinearity and singularity due to the curvature term in
Externí odkaz:
http://arxiv.org/abs/2308.13471
Deep neural network is a powerful tool for many tasks. Understanding why it is so successful and providing a mathematical explanation is an important problem and has been one popular research direction in past years. In the literature of mathematical
Externí odkaz:
http://arxiv.org/abs/2307.09052
For problems in image processing and many other fields, a large class of effective neural networks has encoder-decoder-based architectures. Although these networks have made impressive performances, mathematical explanations of their architectures ar
Externí odkaz:
http://arxiv.org/abs/2307.09039
Solution methods for the nonlinear partial differential equation of the Rudin-Osher-Fatemi (ROF) and minimum-surface models are fundamental for many modern applications. Many efficient algorithms have been proposed. First order methods are common. Th
Externí odkaz:
http://arxiv.org/abs/2208.01390