{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T08:27:36Z","timestamp":1765268856544},"reference-count":24,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,10,16]],"date-time":"2022-10-16T00:00:00Z","timestamp":1665878400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,16]],"date-time":"2022-10-16T00:00:00Z","timestamp":1665878400000},"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":[[2022,10,16]]},"DOI":"10.1109\/icip46576.2022.9897419","type":"proceedings-article","created":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T21:27:24Z","timestamp":1667510844000},"page":"4153-4157","source":"Crossref","is-referenced-by-count":5,"title":["Multi-Step Test-Time Adaptation with Entropy Minimization and Pseudo-Labeling"],"prefix":"10.1109","author":[{"given":"Hiroaki","family":"Kingetsu","sequence":"first","affiliation":[{"name":"Fujitsu Limited,AI Laboratory,Kanagawa,Japan"}]},{"given":"Kenichi","family":"Kobayashi","sequence":"additional","affiliation":[{"name":"Fujitsu Limited,AI Laboratory,Kanagawa,Japan"}]},{"given":"Yoshihiro","family":"Okawa","sequence":"additional","affiliation":[{"name":"Fujitsu Limited,AI Laboratory,Kanagawa,Japan"}]},{"given":"Yasuto","family":"Yokota","sequence":"additional","affiliation":[{"name":"Fujitsu Limited,AI Laboratory,Kanagawa,Japan"}]},{"given":"Katsuhito","family":"Nakazawa","sequence":"additional","affiliation":[{"name":"Fujitsu Limited,AI Laboratory,Kanagawa,Japan"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/9780262170055.001.0001"},{"article-title":"Intriguing properties of neural networks","year":"2014","author":"Szegedy","key":"ref2"},{"article-title":"Benchmarking neural network robustness to common corruptions and perturbations","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Hendrycks","key":"ref3"},{"article-title":"Generalisation in humans and deep neural networks","volume-title":"Proceedings of the 32nd International Conference on Neural Information Processing Systems","author":"Geirhos","key":"ref4"},{"article-title":"Test-Time Training with Self-Supervision for Generalization under Distribution Shifts","volume-title":"37th International Conference on Ma-chine Learning, ICML 2020","author":"Sun","key":"ref5"},{"article-title":"How transferable are features in deep neural networks?","volume-title":"Proceedings of the 27th International Conference on Neural Information Processing Systems","author":"Yosinski","key":"ref6"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00966"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00460"},{"article-title":"Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation","volume-title":"37th International Conference on Machine Learning, ICML 2020","author":"Liang","key":"ref9"},{"article-title":"Tent: Fully test-time adaptation by entropy minimization","volume-title":"International Conference on Learning Representations (ICLR)","author":"Wang","key":"ref10"},{"article-title":"Semi-supervised learning by entropy minimization","volume-title":"NIPS\u201904","author":"Grandvalet","key":"ref11"},{"article-title":"Dis-criminative clustering by Regularized Information Maximization","volume-title":"Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems, NIPS 2010","author":"Gomes","key":"ref12"},{"article-title":"Information-theoretical learning of discriminative clusters for unsupervised domain adaptation","volume-title":"Proceedings of the 29th International Conference on Machine Learning, ICML 2012","author":"Shi","key":"ref13"},{"article-title":"Learning discrete representations via information maximizing self-augmented training","volume-title":"34th International Conference on Machine Learning, ICML 2017","author":"Hu","key":"ref14"},{"article-title":"A DIRT-t approach to unsupervised domain adaptation","volume-title":"6th International Conference on Learning Representations (ICLR)","author":"Shu","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2858821"},{"article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","volume-title":"ICML 2013 Workshop: Challenges in Representation Learning","author":"Lee","key":"ref17"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00753"},{"article-title":"AugMix: A simple data processing method to improve robustness and uncertainty","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Hendrycks","key":"ref19"},{"article-title":"Learning multiple layers of features from tiny images","year":"2009","author":"Krizhevsky","key":"ref20"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.5244\/C.30.87"},{"article-title":"Improving robustness against common corruptions by covariate shift adaptation","year":"2020","author":"Schneider","key":"ref23"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.03.005"}],"event":{"name":"2022 IEEE International Conference on Image Processing (ICIP)","start":{"date-parts":[[2022,10,16]]},"location":"Bordeaux, France","end":{"date-parts":[[2022,10,19]]}},"container-title":["2022 IEEE International Conference on Image Processing (ICIP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9897158\/9897159\/09897419.pdf?arnumber=9897419","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T21:35:05Z","timestamp":1705959305000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9897419\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,16]]},"references-count":24,"URL":"https:\/\/doi.org\/10.1109\/icip46576.2022.9897419","relation":{},"subject":[],"published":{"date-parts":[[2022,10,16]]}}}