{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:23:25Z","timestamp":1740101005916,"version":"3.37.3"},"reference-count":42,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100011790","name":"Xiangya Hospital Central South University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011790","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7,18]]},"DOI":"10.1109\/ijcnn55064.2022.9892015","type":"proceedings-article","created":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T19:56:04Z","timestamp":1664567764000},"page":"1-7","source":"Crossref","is-referenced-by-count":1,"title":["Marrying Convolution and Transformer for COVID-19 Diagnosis Based on CT Scans"],"prefix":"10.1109","author":[{"given":"Jie","family":"Mei","sequence":"first","affiliation":[{"name":"College of Computer, National University of Defense Technology,Changsha,China"}]}],"member":"263","reference":[{"key":"ref39","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","author":"chen","year":"0","journal-title":"International Conference on Machine Learning"},{"key":"ref38","first-page":"9912","article-title":"Unsupervised learning of visual features by contrasting cluster assignments","volume":"33","author":"caron","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref32","first-page":"315","article-title":"Deep sparse rectifier neural networks","author":"glorot","year":"0","journal-title":"Proceedings of the fourteenth international conference on artificial intelligence and statistics JMLR Workshop and Conference Proceedings"},{"key":"ref31","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"0","journal-title":"International Conference on Machine Learning"},{"key":"ref30","article-title":"Improved baselines with momentum contrastive learning","author":"chen","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01549"},{"key":"ref36","first-page":"21271","article-title":"Bootstrap your own latent-a new approach to self-supervised learning","volume":"33","author":"grill","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref35","first-page":"arxiv-1807","article-title":"Representation learning with contrastive predictive coding","author":"van den oord","year":"2018","journal-title":"ArXiv e-prints"},{"key":"ref34","article-title":"Layer normalization","author":"ba","year":"2016","journal-title":"ArXiv Preprint"},{"key":"ref10","article-title":"Deep residual learning for image recognition","volume":"abs 1512 3385","author":"he","year":"2015","journal-title":"CoRR"},{"key":"ref11","article-title":"Densely connected convolutional networks","author":"huang","year":"2016","journal-title":"IEEE Computer Society"},{"key":"ref40","article-title":"Covid-ct-dataset: a ct scan dataset about covid-19","author":"zhao","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref12","article-title":"An image is worth 16&#x00D7;16 words: Transformers for image recognition at scale","author":"dosovitskiy","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ISPCC53510.2021.9609375"},{"key":"ref15","article-title":"Covid-vit: Classification of covid-19 from ct chest images based on vision transformer models","author":"gao","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref16","article-title":"A battle of network structures: An empirical study of cnn, transformer, and mlp","author":"zhao","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref17","article-title":"Is it time to replace cnns with transformers for medical images?","author":"matsoukas","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref18","article-title":"Transunet: Transformers make strong encoders for medical image segmentation","author":"chen","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref19","article-title":"Transformer-unet: Raw image processing with unet","author":"sha","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref4","article-title":"Automatic Detection of Coronavirus Disease (COVID-19) Using X-ray Images and Deep Convolutional Neural Networks","author":"narin","year":"2020","journal-title":"ArXiv e-prints"},{"key":"ref28","article-title":"Swintrack: A simple and strong baseline for transformer tracking","author":"lin","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"19549","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","volume":"10","author":"wang","year":"2020","journal-title":"Scientific Reports"},{"key":"ref27","article-title":"Swin-unet: Unet-like pure transformer for medical image segmentation","author":"cao","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2993291"},{"key":"ref5","article-title":"Rapid AI Development Cycle for the Coronavirus (COVID-19) Pandemic: Initial Results for Automated Detection & Patient Monitoring using Deep Learning CT Image Analysis","author":"gozes","year":"2020","journal-title":"ArXiv e-prints"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref8","article-title":"Sample-efficient deep learning for covid-19 diagnosis based on ct scans","author":"he","year":"2020","journal-title":"medRxiv"},{"key":"ref7","article-title":"Covidctnet: An open-source deep learning approach to identify covid-19 using ct image","author":"javaheri","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2993291"},{"key":"ref9","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","volume":"25","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"},{"journal-title":"Covid-19 real-time big data report","year":"2021","author":"baidu","key":"ref1"},{"key":"ref20","article-title":"nnformer: Interleaved transformer for volumetric segmentation","author":"zhou","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref22","article-title":"Coatnet: Marrying convolution and attention for all data sizes","author":"dai","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01625"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref24","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"ArXiv Preprint"},{"key":"ref41","article-title":"Clinically applicable ai system for accurate diagnosis, quantitative measurements, and prognosis of covid-19 pneumonia using computed tomography - sciencedirect","author":"zhang","year":"0","journal-title":"Cell"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00950"},{"key":"ref26","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"0","journal-title":"Advances in neural information processing systems"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"}],"event":{"name":"2022 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2022,7,18]]},"location":"Padua, Italy","end":{"date-parts":[[2022,7,23]]}},"container-title":["2022 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9891857\/9889787\/09892015.pdf?arnumber=9892015","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T20:52:51Z","timestamp":1665780771000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9892015\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,18]]},"references-count":42,"URL":"https:\/\/doi.org\/10.1109\/ijcnn55064.2022.9892015","relation":{},"subject":[],"published":{"date-parts":[[2022,7,18]]}}}