Zobrazeno 1 - 10
of 15 427
pro vyhledávání: '"Wang, Shuang"'
This study presents ResVMUNetX, a novel image enhancement network for low-light conditions, addressing the limitations of existing deep learning methods in capturing long-range image information. Leveraging error regression and an efficient VMamba ar
Externí odkaz:
http://arxiv.org/abs/2407.09553
Addressing the imperative need for efficient artificial intelligence in IoT and edge computing, this study presents RepAct, a re-parameterizable adaptive activation function tailored for optimizing lightweight neural networks within the computational
Externí odkaz:
http://arxiv.org/abs/2407.00131
Autor:
Huang, De-Xing, Zhou, Xiao-Hu, Xie, Xiao-Liang, Liu, Shi-Qi, Wang, Shuang-Yi, Feng, Zhen-Qiu, Gui, Mei-Jiang, Li, Hao, Xiang, Tian-Yu, Yao, Bo-Xian, Hou, Zeng-Guang
Automatic vessel segmentation is paramount for developing next-generation interventional navigation systems. However, current approaches suffer from suboptimal segmentation performances due to significant challenges in intraoperative images (i.e., lo
Externí odkaz:
http://arxiv.org/abs/2406.19749
Publikováno v:
(2024 Conference on Computer Vision and Pattern Recognition)
We study source-free unsupervised domain adaptation (SFUDA) for semantic segmentation, which aims to adapt a source-trained model to the target domain without accessing the source data. Many works have been proposed to address this challenging proble
Externí odkaz:
http://arxiv.org/abs/2406.06813
Autor:
Yang, Rui, Wang, Shuang, Han, Yingping, Li, Yuanheng, Zhao, Dong, Quan, Dou, Guo, Yanhe, Jiao, Licheng
Remote Sensing Image-Text Retrieval (RSITR) is pivotal for knowledge services and data mining in the remote sensing (RS) domain. Considering the multi-scale representations in image content and text vocabulary can enable the models to learn richer re
Externí odkaz:
http://arxiv.org/abs/2405.18959
Autor:
Wang, Shuang, Kang, Wanying
The non-Oberbeck--Boussinesq (NOB) effects arising from variations in thermal expansivity are theoretically and numerically studied in the context of rotating Rayleigh--B\'{e}nard convection in forms of two-dimensional (2D) rolls. The thermal expansi
Externí odkaz:
http://arxiv.org/abs/2405.01721
Low-dose computed tomography (LDCT) has become the technology of choice for diagnostic medical imaging, given its lower radiation dose compared to standard CT, despite increasing image noise and potentially affecting diagnostic accuracy. To address t
Externí odkaz:
http://arxiv.org/abs/2404.09533
In 2021, a new charm-strange meson, $D_{s0}(2590)^+$, has been discovered, it is believed to be the $D_s^+(2^1S_0)$. However, its low mass and wide width are challenged by theoretical results. Given the small branching ratio of the current production
Externí odkaz:
http://arxiv.org/abs/2404.08167
Geographical, physical, or economic constraints often result in missing traces within seismic data, making the reconstruction of complete seismic data a crucial step in seismic data processing. Traditional methods for seismic data reconstruction requ
Externí odkaz:
http://arxiv.org/abs/2403.11482
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 4, p e18948 (2020)
BackgroundCoronavirus disease (COVID-19) has been an unprecedented challenge to the global health care system. Tools that can improve the focus of surveillance efforts and clinical decision support are of paramount importance. ObjectiveThe aim of th
Externí odkaz:
https://doaj.org/article/50629a40482243619bca9529846ad9de