RESCOVIDTCNnet: A residual neural network-based framework for COVID-19 detection using TCN and EWT with chest X-ray images

作者：

Highlights：

• Automated detection of COVID-19 using chest X-ray chest images.

• Proposed novel deep learning model : RESCOVIDTCNNet.

• EWT was used to pre-process the chest X-rays images.

• Model was developed using all available public datasets.

• Proposed method obtained highest classification accuracy of 99.5%.

摘要

•Automated detection of COVID-19 using chest X-ray chest images.•Proposed novel deep learning model : RESCOVIDTCNNet.•EWT was used to pre-process the chest X-rays images.•Model was developed using all available public datasets.•Proposed method obtained highest classification accuracy of 99.5%.

论文关键词：COVID-19 diagnosis,X-ray Lung images,Pre-trained CNN methods: Inception-V3 & Resnet-50,TCN,EWT

论文评审过程：Received 21 November 2021, Revised 7 April 2022, Accepted 25 April 2022, Available online 28 April 2022, Version of Record 9 June 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117410