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High-fidelity 3D anatomical reconstruction is essential for clinical applications, yet converting voxel-based segmentation into smooth and watertight meshes remains challenging due to noise, incompleteness, and shape variability. We propose Med-PU, a knowledge-driven framework that integrates volumetric segmentation with deep point cloud upsampling …
cn (code pays fourni par la source)
hk, cn (code pays fourni par la source)
Yixin Chen, Ren Xu, Andrew Lau, Xinjie He et autres
cn, pt, at, pl (code pays fourni par la source)
With the development of information technology, the market's demand for precise indoor positioning is increasing. Radio frequency identification (RFID) has always been paid extensive attention from researchers in the field of indoor positioning, but the problem of difficulty in balancing system cost …
cn (code pays fourni par la source)
SiQi Wang, Xing Hu, Bei Wang, WenXin Yao et autres
With the rapid development of deep learning, the implementation of intricate algorithms and substantial data processing have become standard elements of deep learning projects. As a result, the code has become progressively complex as the software evolves, which is difficult to maintain …
Zishan Wang, Ruqiang Huang, Lei Zhang, Shaokai Zhao et autres
cn (code pays fourni par la source)
In recent years, automatic sleep staging models based on artificial intelligence have been developed to provide physicians with more efficient diagnostic assistance support. However, the performance of automatic sleep staging models is limited by several problems such as insufficient available training data …
cn (code pays fourni par la source)
Sleep staging is a critical task in sleep medicine, aiding in the diagnosis and treatment of sleep disorders such as Obstructive Sleep Apnea (OSA). The presence of significant differences in patient recovery during OSA treatment results in substantial variations in data distribution, …
cn (code pays fourni par la source)
Zishan Wang, Ruqiang Huang, Ye Yan, Zhiguo Luo et autres
(1) Background: Emotion recognition based on EEG signals is a rapidly growing and promising research field in affective computing. However, traditional methods have focused on single-channel features that reflect time-domain or frequency-domain information of the EEG, as well as bi-channel features that …
cn (code pays fourni par la source)
Abstract In recent years, multitudes of researches have applied deep learning to automatic sleep stage classification. Whereas actually, these works have paid less attention to the issue of cross-subject in sleep staging. At the same time, emerging neuroscience theories on inter-subject correlations …
cn (code pays fourni par la source)
In recent years, multitudes of researches have applied deep learning to automatic sleep stage classification. Whereas actually, these works have paid less attention to the issue of cross-subject in sleep staging. At the same time, emerging neuroscience theories on inter-subject correlations can …
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