Momentum contrast transformer for COVID-19 diagnosis with knowledge distillation [0.03%]
具有知识蒸馏的动量对比变换器用于COVID-19诊断
Aimei Dong,Jian Liu,Guodong Zhang et al.
Aimei Dong et al.
Intelligent diagnosis has been widely studied in diagnosing novel corona virus disease (COVID-19). Existing deep models typically do not make full use of the global features such as large areas of ground glass opacities, and the local featu...
Quantifying the Preferential Direction of the Model Gradient in Adversarial Training With Projected Gradient Descent [0.03%]
具有投影梯度下降的对抗训练中模型梯度偏向方向的量化方法
Ricardo Bigolin Lanfredi,Joyce D Schroeder,Tolga Tasdizen
Ricardo Bigolin Lanfredi
Adversarial training, especially projected gradient descent (PGD), has proven to be a successful approach for improving robustness against adversarial attacks. After adversarial training, gradients of models with respect to their inputs hav...
Deep learning of longitudinal mammogram examinations for breast cancer risk prediction [0.03%]
基于纵向乳腺X线摄影检查的深度学习乳腺癌风险预测模型
Saba Dadsetan,Dooman Arefan,Wendie A Berg et al.
Saba Dadsetan et al.
Information in digital mammogram images has been shown to be associated with the risk of developing breast cancer. Longitudinal breast cancer screening mammogram examinations may carry spatiotemporal information that can enhance breast canc...
Invariance encoding in sliced-Wasserstein space for image classification with limited training data [0.03%]
有限训练数据下的图像分类的切片Wasserstein不变量编码方法
Mohammad Shifat-E-Rabbi,Yan Zhuang,Shiying Li et al.
Mohammad Shifat-E-Rabbi et al.
Deep convolutional neural networks (CNNs) are broadly considered to be state-of-the-art generic end-to-end image classification systems. However, they are known to underperform when training data are limited and thus require data augmentati...
Fadi Boutros,Naser Damer,Florian Kirchbuchner et al.
Fadi Boutros et al.
Using the face as a biometric identity trait is motivated by the contactless nature of the capture process and the high accuracy of the recognition algorithms. After the current COVID-19 pandemic, wearing a face mask has been imposed in pub...
A multi-task fully deep convolutional neural network for contactless fingerprint minutiae extraction [0.03%]
用于非接触指纹纹 minutiae提取的多任务全深度卷积神经网络
Zhao Zhang,Shuxin Liu,Manhua Liu
Zhao Zhang
With the outbreak and wide spread of novel coronavirus (COVID-19), contactless fingerprint recognition has attracted more attention for personal recognition because it can provide significantly higher user convenience and hygiene than the t...
Ibrahim M Hezam,Abdulkarem Almshnanah,Ahmed A Mubarak et al.
Ibrahim M Hezam et al.
Unfortunately, the COVID-19 outbreak has been accompanied by the spread of rumors and depressing news. Herein, we develop a dynamic nested optimal control model of COVID-19 and its rumor outbreaks. The model aims to curb the epidemics by re...
Baojin Huang,Zhongyuan Wang,Guangcheng Wang et al.
Baojin Huang et al.
The outbreak of the COVID-19 coronavirus epidemic has promoted the development of masked face recognition (MFR). Nevertheless, the performance of regular face recognition is severely compromised when the MFR accuracy is blindly pursued. Mor...
GFNet: Automatic segmentation of COVID-19 lung infection regions using CT images based on boundary features [0.03%]
基于边界特征的CT图像新冠肺炎病灶分割网络GFNet
Chaodong Fan,Zhenhuan Zeng,Leyi Xiao et al.
Chaodong Fan et al.
In early 2020, the global spread of the COVID-19 has presented the world with a serious health crisis. Due to the large number of infected patients, automatic segmentation of lung infections using computed tomography (CT) images has great p...
COVID-19 contact tracking by group activity trajectory recovery over camera networks [0.03%]
基于摄像头网络的群体活动轨迹恢复接触追踪方法应对新冠肺炎疫情
Chao Wang,XiaoChen Wang,Zhongyuan Wang et al.
Chao Wang et al.
Contact tracking plays an important role in the epidemiological investigation of COVID-19, which can effectively reduce the spread of the epidemic. As an excellent alternative method for contact tracking, mobile phone location-based methods...