{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:06:59Z","timestamp":1740100019215,"version":"3.37.3"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T00:00:00Z","timestamp":1620950400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T00:00:00Z","timestamp":1620950400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-009"},{"start":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T00:00:00Z","timestamp":1620950400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-001"}],"funder":[{"DOI":"10.13039\/501100019054","name":"Changsha Science and Technology Project","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100019054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5,14]]},"DOI":"10.1109\/icaci52617.2021.9435874","type":"proceedings-article","created":{"date-parts":[[2021,5,25]],"date-time":"2021-05-25T20:12:01Z","timestamp":1621973521000},"page":"318-322","source":"Crossref","is-referenced-by-count":2,"title":["COVID-19 Patients Detection in Chest X-ray Images via MCFF-Net"],"prefix":"10.1109","author":[{"given":"Wei","family":"Wang","sequence":"first","affiliation":[]},{"given":"Yutao","family":"Li","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Ji","family":"Li","sequence":"additional","affiliation":[]},{"given":"Peng","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications[J]","author":"howard","year":"2017","journal-title":"arXiv preprint arXiv 1704 04861"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.103792"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2020.105581"},{"key":"ref13","first-page":"1251","article-title":"Xception: Deep learning with depthwise separable convolutions[C]","author":"chollet","year":"2017","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref14","article-title":"Network in network[J]","author":"lin","year":"2013","journal-title":"arXiv preprint arXiv 1312 4400"},{"key":"ref15","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift[C]","author":"ioffe","year":"2015","journal-title":"International Conference on Machine Learning"},{"key":"ref16","article-title":"Empirical evaluation of rectified activations in convolutional network[J]","author":"xu","year":"2015","journal-title":"arXiv preprint arXiv 1505 00853"},{"key":"ref17","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks[J]","volume":"25","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"},{"journal-title":"Covid-chestxray-dataset","year":"2020","author":"cohen","key":"ref18"},{"journal-title":"Chest-X Ray Images(Pneumonia)","year":"0","author":"mooney","key":"ref19"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/7602384"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1186\/s12880-020-00482-3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.2991\/ijcis.d.201123.001"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.2991\/ijcis.d.200910.001"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s13246-020-00865-4"},{"key":"ref7","article-title":"Very deep convolutional networks for large-scale image recognition[J]","author":"simonyan","year":"2014","journal-title":"arXiv preprint arXiv 1409 1556"},{"journal-title":"Use of chest imaging in COVID-19 a rapid advice guide","article-title":"World Health Organization","year":"2020","key":"ref2"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2020200490"},{"key":"ref9","first-page":"1","article-title":"Covid-net: A tailored deep convolutional neural network design for detection of covid-19 cases from chest x-ray images[J]","volume":"10","author":"wang","year":"2020","journal-title":"Scientific Reports"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref21","first-page":"4700","article-title":"Densely connected convolutional networks[C]","author":"huang","year":"2017","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"}],"event":{"name":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","start":{"date-parts":[[2021,5,14]]},"location":"Wanzhou, China","end":{"date-parts":[[2021,5,16]]}},"container-title":["2021 13th International Conference on Advanced Computational Intelligence (ICACI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9435848\/9435857\/09435874.pdf?arnumber=9435874","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:41:49Z","timestamp":1652197309000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9435874\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,14]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/icaci52617.2021.9435874","relation":{},"subject":[],"published":{"date-parts":[[2021,5,14]]}}}