{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T09:11:07Z","timestamp":1725613867743},"reference-count":34,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,6,30]],"date-time":"2021-06-30T00:00:00Z","timestamp":1625011200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,6,30]],"date-time":"2021-06-30T00:00:00Z","timestamp":1625011200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,6,30]],"date-time":"2021-06-30T00:00:00Z","timestamp":1625011200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,6,30]]},"DOI":"10.1109\/jcsse53117.2021.9493846","type":"proceedings-article","created":{"date-parts":[[2021,7,27]],"date-time":"2021-07-27T21:05:56Z","timestamp":1627419956000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["COVID-19 Classification using DCNNs and Exploration Correlation using Canonical Correlation Analysis"],"prefix":"10.1109","author":[{"given":"Rujira","family":"Jullapak","sequence":"first","affiliation":[]},{"given":"Tongjai","family":"Yampaka","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-020-03626-y"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.07.075"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.7763\/IJCTE.2011.V3.328"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/4670187"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.20.23304"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3195588.3195597"},{"article-title":"COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest Radiography Images","year":"2020","author":"lindawang","key":"ref12"},{"journal-title":"Using Deep Learning to Detect Pneumonia Caused by NCOV-19 From X-Ray Images","year":"2020","author":"joaquin","key":"ref13"},{"article-title":"Opening the black box of deep neural networks via information","year":"2017","author":"shwartz-ziv","key":"ref14"},{"key":"ref15","article-title":"On the Information bottleneck theory of deep Learning","author":"saxe","year":"2018","journal-title":"Proceedings of the International Conference on Learning Representations"},{"article-title":"Dynamic learning rate using Mutual Information","year":"2018","author":"vasudevan","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2018.01185"},{"article-title":"Learning deep representations by mutual information estimation and maximization","year":"2018","author":"hjelm","key":"ref18"},{"key":"ref19","doi-asserted-by":"crossref","DOI":"10.1613\/jair.1.12162","article-title":"Mapping the Landscape of Artificial Intelligence Applications against COVID-19","author":"bullock","year":"2020"},{"key":"ref28","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-020-76550-z","article-title":"COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-ray Images","author":"wang","year":"2020"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30211-7"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-35488-8_5"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2020.1585"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30183-5"},{"article-title":"DeepCOVIDExplainer: Explainable COVID-19 Predictions Based on Chest X-ray Images","year":"2020","author":"karim","key":"ref29"},{"key":"ref5","doi-asserted-by":"crossref","DOI":"10.1056\/NEJMoa2001316","article-title":"Early transmission dynamics in Wuhan, China, of novel coronavirus– infected pneumonia","author":"li","year":"2020","journal-title":"New England Journal of Medicine"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.01.006"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3390\/app10020559"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics10030165"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0207982"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2020.3786"},{"key":"ref20","first-page":"200642","article-title":"Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases","author":"ai","year":"2020","journal-title":"Radiology"},{"article-title":"Automatic Detection of Coronavirus Disease (COVID-19) Using X-ray Images and Deep Convolutional Neural Networks","year":"2020","author":"narin","key":"ref22"},{"article-title":"Estimating Uncertainty and Interpretability in Deep Learning for Coronavirus (COVID-19) Detection","year":"2020","author":"ghoshal","key":"ref21"},{"journal-title":"Open database of covid-19 cases with chest x-ray or ct images","year":"0","key":"ref24"},{"key":"ref23","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-020-76550-z","article-title":"COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Images","author":"wang","year":"2020"},{"article-title":"MINE: Mutual Information Neural Estimation","year":"2020","author":"belghazi","key":"ref26"},{"journal-title":"Chest X-Ray Images (Pneumonia)","year":"0","key":"ref25"}],"event":{"name":"2021 18th International Joint Conference on Computer Science and Software Engineering (JCSSE)","start":{"date-parts":[[2021,6,30]]},"location":"Lampang, Thailand","end":{"date-parts":[[2021,7,2]]}},"container-title":["2021 18th International Joint Conference on Computer Science and Software Engineering (JCSSE)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9493665\/9493804\/09493846.pdf?arnumber=9493846","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,5]],"date-time":"2023-01-05T17:50:39Z","timestamp":1672941039000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9493846\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,30]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/jcsse53117.2021.9493846","relation":{},"subject":[],"published":{"date-parts":[[2021,6,30]]}}}