{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T12:07:26Z","timestamp":1730203646940,"version":"3.28.0"},"reference-count":31,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,11,26]],"date-time":"2022-11-26T00:00:00Z","timestamp":1669420800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,11,26]],"date-time":"2022-11-26T00:00:00Z","timestamp":1669420800000},"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":[[2022,11,26]]},"DOI":"10.1109\/ccis57298.2022.10016411","type":"proceedings-article","created":{"date-parts":[[2023,1,19]],"date-time":"2023-01-19T14:08:53Z","timestamp":1674137333000},"page":"590-595","source":"Crossref","is-referenced-by-count":0,"title":["Re-weighting and Hierarchical Pre-training Boost 3D Medical Self-Supervised Representation"],"prefix":"10.1109","author":[{"given":"Shouyu","family":"Chen","sequence":"first","affiliation":[{"name":"Tongji University,College of Electronics and Information Engineering,Department of Computer Science and Technology,Shanghai,China"}]},{"given":"Yin","family":"Wang","sequence":"additional","affiliation":[{"name":"Tongji University,College of Electronics and Information Engineering,Department of Computer Science and Technology,Shanghai,China"}]},{"given":"Ke","family":"Sun","sequence":"additional","affiliation":[{"name":"Fudan University,Huashan Hospital,Department of Radiology,Shanghai,China"}]},{"given":"Xiwen","family":"Sun","sequence":"additional","affiliation":[{"name":"Tongji University School of Medicine,Shanghai Pulmonary Hospital,Department of Radiology,Shanghai,China"}]}],"member":"263","reference":[{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32251-9_42"},{"key":"ref30","first-page":"11842","article-title":"Delving into deep imbalanced regression","author":"yang","year":"2021","journal-title":"International Conference on Machine Learning"},{"key":"ref10","article-title":"Bootstrap your own latent: A new approach to self-supervised learning","author":"grill","year":"2020","journal-title":"arXiv preprint arXiv 2006 07529"},{"key":"ref11","first-page":"1322","article-title":"Adasyn: Adaptive synthetic sampling approach for imbalanced learning","author":"he","year":"2008","journal-title":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1186\/s41747-020-00173-2"},{"key":"ref14","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"International Conference on Machine Learning"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3390\/technologies9010002"},{"key":"ref16","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv preprint arXiv 1412 6980"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2016.2635663"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87196-3_4"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2377694"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87196-3_9"},{"key":"ref4","first-page":"22243","article-title":"Bigself-supervised models are strong semi-supervised learners","volume":"33","author":"chen","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32226-7_20"},{"key":"ref3","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","author":"chen","year":"2020","journal-title":"International Conference on Machine Learning"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01549"},{"key":"ref29","first-page":"3733","article-title":"Unsupervised feature learning via nonparametric instance discrimination","author":"wu","year":"2018","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref5","article-title":"Improved baselines with momentum contrastive learning","author":"chen","year":"2020","journal-title":"arXiv preprint arXiv 2003 04297"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2832629"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-013-9622-7"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"101797","DOI":"10.1016\/j.media.2020.101797","article-title":"Padchest: A large chest x-ray image dataset with multi-label annotated reports","volume":"66","author":"bustos","year":"2020","journal-title":"Medical Image Analysis"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87234-2_29"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32226-7_28"},{"key":"ref20","article-title":"Mixed precision training","author":"micikevicius","year":"2017","journal-title":"arXiv preprint arXiv 1710 03740"},{"key":"ref22","article-title":"Byol works even without batch statistics","author":"richemond","year":"2020","journal-title":"arXiv preprint arXiv 2010 10042"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00112"},{"key":"ref24","article-title":"What makes for good views for contrastive learning?","author":"tian","year":"2020","journal-title":"arXiv preprint arXiv 2005 10545"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.105002"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2791721"},{"key":"ref25","article-title":"Pushing the limits of self-supervised resnets: Can we outperform supervised learning without labels on imagenet?","author":"tomasev","year":"2022","journal-title":"arXiv preprint arXiv 2201 05119"}],"event":{"name":"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","start":{"date-parts":[[2022,11,26]]},"location":"Chengdu, China","end":{"date-parts":[[2022,11,28]]}},"container-title":["2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10016307\/10016308\/10016411.pdf?arnumber=10016411","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T16:57:57Z","timestamp":1676912277000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10016411\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,26]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/ccis57298.2022.10016411","relation":{},"subject":[],"published":{"date-parts":[[2022,11,26]]}}}