{"title":"基于深度迁移学习的COVID-19识别","authors":"Soulef Bouaafia, Seifeddine Messaoud, Randa Khemiri, Fatma Sayadi","doi":"10.1109/DTS52014.2021.9498052","DOIUrl":null,"url":null,"abstract":"With the rapid development technology, Artificial Intelligence is the most powerful technique, it has made great progress in many areas, including computer vision and medical imaging. This paper proposes a deep learning-based framework for COVID-19 detection. Deep transfer learning models-based on a pre-trained Deep convolutional Neural Network are proposed. Several pre-trained models, such as DensNet201, InceptionV3, VGG16, and ResNet50 were evaluated for this analysis.The datasets used in this paper for training model are a mix of X-ray and CT images in two distinct categories: Normal and COVID-19. The experimental results proved that the DensNet201 was the most suitable deep transfer model according to the test accuracy measure and that it reached 97% with the other performance metrics such as F1 score, precision, and recall.","PeriodicalId":158426,"journal":{"name":"2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"COVID-19 Recognition based on Deep Transfer Learning\",\"authors\":\"Soulef Bouaafia, Seifeddine Messaoud, Randa Khemiri, Fatma Sayadi\",\"doi\":\"10.1109/DTS52014.2021.9498052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid development technology, Artificial Intelligence is the most powerful technique, it has made great progress in many areas, including computer vision and medical imaging. This paper proposes a deep learning-based framework for COVID-19 detection. Deep transfer learning models-based on a pre-trained Deep convolutional Neural Network are proposed. Several pre-trained models, such as DensNet201, InceptionV3, VGG16, and ResNet50 were evaluated for this analysis.The datasets used in this paper for training model are a mix of X-ray and CT images in two distinct categories: Normal and COVID-19. The experimental results proved that the DensNet201 was the most suitable deep transfer model according to the test accuracy measure and that it reached 97% with the other performance metrics such as F1 score, precision, and recall.\",\"PeriodicalId\":158426,\"journal\":{\"name\":\"2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS)\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DTS52014.2021.9498052\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DTS52014.2021.9498052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
COVID-19 Recognition based on Deep Transfer Learning
With the rapid development technology, Artificial Intelligence is the most powerful technique, it has made great progress in many areas, including computer vision and medical imaging. This paper proposes a deep learning-based framework for COVID-19 detection. Deep transfer learning models-based on a pre-trained Deep convolutional Neural Network are proposed. Several pre-trained models, such as DensNet201, InceptionV3, VGG16, and ResNet50 were evaluated for this analysis.The datasets used in this paper for training model are a mix of X-ray and CT images in two distinct categories: Normal and COVID-19. The experimental results proved that the DensNet201 was the most suitable deep transfer model according to the test accuracy measure and that it reached 97% with the other performance metrics such as F1 score, precision, and recall.