151 citations · 157 across the 7 of their papers we have counts for
7 papers
UT-OSANet: A Multimodal Deep Learning model for Evaluating and Classifying Obstructive Sleep Apnea
Zijian Wang, Xiaoyu Bao, Chenhao Zhao +3
Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder that is associated with increased risks of cardiovascular morbidity and all-cause mortality. While existing diagn…
Alleviating Seasickness through Brain-Computer Interface-based Attention Shift
Xiaoyu Bao, Kailin Xu, Jiawei Zhu +4
Seasickness poses a widespread problem that adversely impacts both passenger comfort and the operational efficiency of maritime crews. Although attention shift has been proposed as…
Few-Shot Learning for Annotation-Efficient Nucleus Instance Segmentation
Yu Ming, Zihao Wu, Jie Yang +7
Nucleus instance segmentation from histopathology images suffers from the extremely laborious and expert-dependent annotation of nucleus instances. As a promising solution to this…
Directly wireless communication of human minds via non-invasive brain-computer-metasurface platform
Qian Ma, Wei Gao, Qiang Xiao +13
Brain-computer interfaces (BCIs), invasive or non-invasive, have projected unparalleled vision and promise for assisting patients in need to better their interaction with the surro…
Electromagnetic Source Imaging via a Data-Synthesis-Based Convolutional Encoder-Decoder Network
Gexin Huang, Jiawen Liang, Ke Liu +6
Electromagnetic source imaging (ESI) requires solving a highly ill-posed inverse problem. To seek a unique solution, traditional ESI methods impose various forms of priors that may…
An Iterative Boundary Random Walks Algorithm for Interactive Image Segmentation
Xiaofeng Xie, ZhuLiang Yu, Zhenghui Gu +1
The interactive image segmentation algorithm can provide an intelligent ways to understand the intention of user input. Many interactive methods have the problem of that ask for la…
Recoverability Analysis for Modified Compressive Sensing with Partially Known Support
Jun Zhang, Yuanqing Li, Zhu Liang Yu +1
The recently proposed modified-compressive sensing (modified-CS), which utilizes the partially known support as prior knowledge, significantly improves the performance of recoverin…