X-ray image based COVID-19 detection using evolutionary deep learning approach

作者：

Highlights：

• A novel deep neuroevolution algorithm for detecting COVID-19 from X-ray images.

• Proposing a modified version of the Competitive Swarm Optimizer algorithm.

• Tuning the hyperparameters and architecture of Convolutional Neural Networks.

• Producing excellent results by proposed framework comparing to 23 benchmarks.

摘要

•A novel deep neuroevolution algorithm for detecting COVID-19 from X-ray images.•Proposing a modified version of the Competitive Swarm Optimizer algorithm.•Tuning the hyperparameters and architecture of Convolutional Neural Networks.•Producing excellent results by proposed framework comparing to 23 benchmarks.

论文关键词：COVID-19,Image classification,Coronavirus,Deep neuroevolution learning,Convolutional neural network,K-nearest neighbor classifier

论文评审过程：Received 8 November 2020, Revised 24 December 2021, Accepted 17 March 2022, Available online 30 March 2022, Version of Record 21 April 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116942