ECOVNet：基于EfficientNet的深度卷积神经网络的集成，可从胸部X射线检测COVID-19

本文提出了一个基于EfficientNet的深度卷积神经网络（ECOVNet）集合，用于使用大型胸部X射线数据集检测COVID-19。首先，扩大开放获取的大型胸部X射线集合，然后为EfficientNet提供ImageNet预先训练的权重，并传递经过训练的一些自定义微调顶层，然后通过模型快照的集合对胸部X进行分类-射线对应于COVID-19，正常和肺炎。..

ECOVNet: An Ensemble of Deep Convolutional Neural Networks Based on EfficientNet to Detect COVID-19 From Chest X-rays

This paper proposed an ensemble of deep convolutional neural networks (CNN) based on EfficientNet, named ECOVNet, to detect COVID-19 using a large chest X-ray data set. At first, the open-access large chest X-ray collection is augmented, and then ImageNet pre-trained weights for EfficientNet is transferred with some customized fine-tuning top layers that are trained, followed by an ensemble of model snapshots to classify chest X-rays corresponding to COVID-19, normal, and pneumonia.The predictions of the model snapshots, which are created during a single training, are combined through two ensemble strategies, i.e., hard ensemble and soft ensemble to ameliorate classification performance and generalization in the related task of classifying chest X-rays.