{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:10:39Z","timestamp":1740100239206,"version":"3.37.3"},"reference-count":28,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2019YFB1804500"],"award-info":[{"award-number":["2019YFB1804500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,18]]},"DOI":"10.1109\/ijcnn52387.2021.9533633","type":"proceedings-article","created":{"date-parts":[[2021,9,20]],"date-time":"2021-09-20T21:27:41Z","timestamp":1632173261000},"page":"1-8","source":"Crossref","is-referenced-by-count":0,"title":["CyCo: A Temporal Cycle Consistency Based Labeling Method for Time Series Data"],"prefix":"10.1109","author":[{"given":"Fengrui","family":"Liu","sequence":"first","affiliation":[{"name":"Institute of Computing Technology, Chinese Academy of Sciences"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiyang","family":"Jiang","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology, Chinese Academy of Sciences"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zulong","family":"Diao","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology, Chinese Academy of Sciences"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanbiao","family":"Li","sequence":"additional","affiliation":[{"name":"Computer Network Information Center, Chinese Academy of Sciences"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gaogang","family":"Xie","sequence":"additional","affiliation":[{"name":"Computer Network Information Center, Chinese Academy of Sciences"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","first-page":"385","article-title":"Fast time sequence indexing for arbitrary lp norms","author":"yi","year":"0","journal-title":"VLDB 2000 Proceedings of 26th International Conference on Very Large Data Bases"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1186\/s13677-016-0062-z"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737429"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972832.64"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/2000824.2000827"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/1066157.1066213"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00190"},{"key":"ref17","first-page":"1","article-title":"Feature extraction evaluation for two motor imagery recognition based on common spatial patterns, time-frequency transformations and SVM","author":"murguia","year":"0","journal-title":"2020 International Joint Conference on Neural Networks (IJCNN) 2020"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2019.8900617"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1007\/s10115-017-1090-9","article-title":"Self-labeling techniques for semi-supervised time series classification: an empirical study","volume":"55","author":"castellanos","year":"2018","journal-title":"Knowl Inf Syst"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/2949741.2949758"},{"key":"ref4","first-page":"359","article-title":"Using dynamic time warping to find patterns in time series","author":"berndt","year":"0","journal-title":"Advances in Knowledge Discovery in Databases Papers from the 1994 AAAI Workshop"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339576"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2017.7966039"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9006212"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/B978-012088469-8.50070-X"},{"key":"ref8","first-page":"513","author":"goldberger","year":"2004","journal-title":"Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems NIPS 2004"},{"key":"ref7","first-page":"205","article-title":"Extracting statistical graph features for accurate and efficient time series classification","author":"li","year":"0","journal-title":"Proceedings of the 21th International Conference on Extending Database Technology EDBT 2018"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9206725"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.14778\/2735479.2735481"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-014-0361-2"},{"key":"ref20","first-page":"669","volume":"7","author":"bromley","year":"1993","journal-title":"Signature verification using a “siamese” time delay neural network"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2011.141"},{"key":"ref21","first-page":"321","article-title":"Learning with local and global consistency","author":"zhou","year":"2003","journal-title":"Advances in Neural Information Processing Systems NIPS 2003"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref23","article-title":"Learning to propagate labels: Transductive propagation network for few-shot learning","author":"liu","year":"0","journal-title":"7th International Conference on Learning Representations ICLR 2019"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788611"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00267"}],"event":{"name":"2021 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2021,7,18]]},"location":"Shenzhen, China","end":{"date-parts":[[2021,7,22]]}},"container-title":["2021 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9533266\/9533267\/09533633.pdf?arnumber=9533633","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,2]],"date-time":"2022-08-02T23:33:47Z","timestamp":1659483227000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9533633\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,18]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/ijcnn52387.2021.9533633","relation":{},"subject":[],"published":{"date-parts":[[2021,7,18]]}}}