Cameron Beeche,Jatin P Singh,Joseph K Leader et al.
Cameron Beeche et al.
Objective: To develop and validate a novel convolutional neural network (CNN) termed "Super U-Net" for medical image segmentation. Methods: ...
Expecting individuals' body reaction to Covid-19 based on statistical Naïve Bayes technique [0.03%]
基于统计Naïve Bayes方法预测个体对Covid-19的生理反应分布规律性
Asmaa H Rabie,Nehal A Mansour,Ahmed I Saleh et al.
Asmaa H Rabie et al.
Covid-19, what a strange, unpredictable mutated virus. It has baffled many scientists, as no firm rule has yet been reached to predict the effect that the virus can inflict on people if they are infected with it. Recently, many researches h...
AUCO ResNet: an end-to-end network for Covid-19 pre-screening from cough and breath [0.03%]
用于从咳嗽和呼吸声音中进行新冠肺炎预筛查的端到端AUCO ResNet网络
Vincenzo Dentamaro,Paolo Giglio,Donato Impedovo et al.
Vincenzo Dentamaro et al.
This study presents the Auditory Cortex ResNet (AUCO ResNet), it is a biologically inspired deep neural network especially designed for sound classification and more specifically for Covid-19 recognition from audio tracks of coughs and brea...
Contour-enhanced attention CNN for CT-based COVID-19 segmentation [0.03%]
基于轮廓增强注意的CNN在CT图像COVID-19区域分割中的应用研究
R Karthik,R Menaka,Hariharan M et al.
R Karthik et al.
Accurate detection of COVID-19 is one of the challenging research topics in today's healthcare sector to control the coronavirus pandemic. Automatic data-powered insights for COVID-19 localization from medical imaging modality like chest CT...
Min Zhang,Geoffrey S Young,Yanmei Tie et al.
Min Zhang et al.
In this work we present a framework of designing iterative techniques for image deblurring in inverse problem. The new framework is based on two observations about existing methods. We used Landweber method as the basis to develop and prese...
COVID-MTL: Multitask learning with Shift3D and random-weighted loss for COVID-19 diagnosis and severity assessment [0.03%]
用于新冠肺炎诊断与分级的多任务学习方法 COVID-MTL
Guoqing Bao,Huai Chen,Tongliang Liu et al.
Guoqing Bao et al.
There is an urgent need for automated methods to assist accurate and effective assessment of COVID-19. Radiology and nucleic acid test (NAT) are complementary COVID-19 diagnosis methods. In this paper, we present an end-to-end multitask lea...
Deep co-supervision and attention fusion strategy for automatic COVID-19 lung infection segmentation on CT images [0.03%]
CT图像中自动COVID-19肺感染分割的深度共监督和注意力融合策略
Haigen Hu,Leizhao Shen,Qiu Guan et al.
Haigen Hu et al.
Due to the irregular shapes,various sizes and indistinguishable boundaries between the normal and infected tissues, it is still a challenging task to accurately segment the infected lesions of COVID-19 on CT images. In this paper, a novel s...
Big data directed acyclic graph model for real-time COVID-19 twitter stream detection [0.03%]
实时COVID-19 Twitter流检测的大数据有向无环图模型
Bakhtiar Amen,Syahirul Faiz,Thanh-Toan Do
Bakhtiar Amen
Every day, large-scale data are continuously generated on social media as streams, such as Twitter, which inform us about all events around the world in real-time. Notably, Twitter is one of the effective platforms to update countries leade...
Fitbeat: COVID-19 estimation based on wristband heart rate using a contrastive convolutional auto-encoder [0.03%]
Fitbeat：基于对比卷积自动编码器的手环心率COVID-19估算
Shuo Liu,Jing Han,Estela Laporta Puyal et al.
Shuo Liu et al.
This study proposes a contrastive convolutional auto-encoder (contrastive CAE), a combined architecture of an auto-encoder and contrastive loss, to identify individuals with suspected COVID-19 infection using heart-rate data from participan...
Real masks and spoof faces: On the masked face presentation attack detection [0.03%]
真实的面具和伪造的脸：关于戴面具人脸的呈现攻击检测
Meiling Fang,Naser Damer,Florian Kirchbuchner et al.
Meiling Fang et al.
Face masks have become one of the main methods for reducing the transmission of COVID-19. This makes face recognition (FR) a challenging task because masks hide several discriminative features of faces. Moreover, face presentation attack de...