Lerina Aversano,Mario Luca Bernardi,Marta Cimitile et al.
Lerina Aversano et al.
Research on Coronavirus Disease 2019 (COVID-19) detection methods has increased in the last months as more accurate automated toolkits are required. Recent studies show that CT scan images contain useful information to detect the COVID-19 d...
Face mask recognition from audio: The MASC database and an overview on the mask challenge [0.03%]
戴口罩识别人脸：MASC数据库和口罩挑战概述
Mostafa M Mohamed,Mina A Nessiem,Anton Batliner et al.
Mostafa M Mohamed et al.
The sudden outbreak of COVID-19 has resulted in tough challenges for the field of biometrics due to its spread via physical contact, and the regulations of wearing face masks. Given these constraints, voice biometrics can offer a suitable c...
Weakly Supervised Segmentation of COVID19 Infection with Scribble Annotation on CT Images [0.03%]
基于CT图像草图注释的COVID19弱监督分割研究
Xiaoming Liu,Quan Yuan,Yaozong Gao et al.
Xiaoming Liu et al.
Segmentation of infections from CT scans is important for accurate diagnosis and follow-up in tackling the COVID-19. Although the convolutional neural network has great potential to automate the segmentation task, most existing deep learnin...
BiconNet: An Edge-preserved Connectivity-based Approach for Salient Object Detection [0.03%]
基于边缘保留连接的显著目标检测方法
Ziyun Yang,Somayyeh Soltanian-Zadeh,Sina Farsiu
Ziyun Yang
Salient object detection (SOD) is viewed as a pixel-wise saliency modeling task by traditional deep learning-based methods. A limitation of current SOD models is insufficient utilization of inter-pixel information, which usually results in ...
AI-Based human audio processing for COVID-19: A comprehensive overview [0.03%]
基于人工智能的新冠肺炎人体音频处理技术综述
Gauri Deshpande,Anton Batliner,Björn W Schuller
Gauri Deshpande
The Coronavirus (COVID-19) pandemic impelled several research efforts, from collecting COVID-19 patients' data to screening them for virus detection. Some COVID-19 symptoms are related to the functioning of the respiratory system that influ...
GraphXCOVID: Explainable deep graph diffusion pseudo-Labelling for identifying COVID-19 on chest X-rays [0.03%]
基于深度图扩散伪标签的可解释性方法在胸部X光片上识别新冠肺炎
Angelica I Aviles-Rivero,Philip Sellars,Carola-Bibiane Schönlieb et al.
Angelica I Aviles-Rivero et al.
Can one learn to diagnose COVID-19 under extreme minimal supervision? Since the outbreak of the novel COVID-19 there has been a rush for developing automatic techniques for expert-level disease identification on Chest X-ray data. In particu...
SARS-Net: COVID-19 detection from chest x-rays by combining graph convolutional network and convolutional neural network [0.03%]
结合图卷积网络和卷积神经网络的胸部X光冠状病毒病检测方法SARS-net
Aayush Kumar,Ayush R Tripathi,Suresh Chandra Satapathy et al.
Aayush Kumar et al.
COVID-19 has emerged as one of the deadliest pandemics that has ever crept on humanity. Screening tests are currently the most reliable and accurate steps in detecting severe acute respiratory syndrome coronavirus in a patient, and the most...
Multi-task driven explainable diagnosis of COVID-19 using chest X-ray images [0.03%]
基于胸部X光图像的多任务驱动COVID-19可解释诊断方法
Aakarsh Malhotra,Surbhi Mittal,Puspita Majumdar et al.
Aakarsh Malhotra et al.
With increasing number of COVID-19 cases globally, all the countries are ramping up the testing numbers. While the RT-PCR kits are available in sufficient quantity in several countries, others are facing challenges with limited availability...
Automated delineation of corneal layers on OCT images using a boundary-guided CNN [0.03%]
基于边界引导的CNN在OCT图像上自动划分角膜层
Lei Wang,Meixiao Shen,Qian Chang et al.
Lei Wang et al.
Accurate segmentation of corneal layers depicted on optical coherence tomography (OCT) images is very helpful for quantitatively assessing and diagnosing corneal diseases (e.g., keratoconus and dry eye). In this study, we presented a novel ...
Efficient COVID-19 testing via contextual model based compressive sensing [0.03%]
基于上下文模型的压缩感知有效检测COVID-19
Mehdi Hasaninasab,Mohammad Khansari
Mehdi Hasaninasab
The COVID-19 pandemic is threatening billions of people's life all over the world. As of March 6, 2021, covid-19 has confirmed in 115,653,459 people worldwide. It has also a devastating effect on businesses and social activities. Since ther...