{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T18:49:52Z","timestamp":1778093392483,"version":"3.51.4"},"reference-count":55,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"French Government through the UCAJEDI Investments in the Future Project"},{"DOI":"10.13039\/501100001665","name":"National Research Agency (ANR), and through the 3IA C\u00f4te d\u2019Azur Investments in the Future Project","doi-asserted-by":"publisher","award":["ANR-15-IDEX-01"],"award-info":[{"award-number":["ANR-15-IDEX-01"]}],"id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001665","name":"National Research Agency (ANR), and through the 3IA C\u00f4te d\u2019Azur Investments in the Future Project","doi-asserted-by":"publisher","award":["ANR-19-P3IA-0002"],"award-info":[{"award-number":["ANR-19-P3IA-0002"]}],"id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2023,7]]},"DOI":"10.1109\/tnnls.2021.3132832","type":"journal-article","created":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T20:28:17Z","timestamp":1639772897000},"page":"3371-3384","source":"Crossref","is-referenced-by-count":76,"title":["A Self-Supervised Deep Learning Approach for Blind Denoising and Waveform Coherence Enhancement in Distributed Acoustic Sensing Data"],"prefix":"10.1109","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0634-7078","authenticated-orcid":false,"given":"Martijn","family":"van den Ende","sequence":"first","affiliation":[{"name":"Géoazur Laboratory, IRD, CNRS, Observatoire de la Côte d’Azur, Université Côte d’Azur, Nice, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9698-9364","authenticated-orcid":false,"given":"Itzhak","family":"Lior","sequence":"additional","affiliation":[{"name":"Géoazur Laboratory, IRD, CNRS, Observatoire de la Côte d’Azur, Université Côte d’Azur, Nice, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4827-7987","authenticated-orcid":false,"given":"Jean-Paul","family":"Ampuero","sequence":"additional","affiliation":[{"name":"Géoazur Laboratory, IRD, CNRS, Observatoire de la Côte d’Azur, Université Côte d’Azur, Nice, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4126-0020","authenticated-orcid":false,"given":"Anthony","family":"Sladen","sequence":"additional","affiliation":[{"name":"Géoazur Laboratory, IRD, CNRS, Observatoire de la Côte d’Azur, Université Côte d’Azur, Nice, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7297-7625","authenticated-orcid":false,"given":"Andr\u00e9","family":"Ferrari","sequence":"additional","affiliation":[{"name":"Observatoire de la Côte d’Azur, UMR Lagrange, Université Côte d’Azur, Nice, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2890-141X","authenticated-orcid":false,"given":"C\u00e9dric","family":"Richard","sequence":"additional","affiliation":[{"name":"Observatoire de la Côte d’Azur, UMR Lagrange, Université Côte d’Azur, Nice, France"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1201\/9781315119014"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-017-11986-4"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1029\/2019gl086115"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1126\/science.aay5881"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-13793-z"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1126\/science.aat4458"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-36675-8"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.5194\/se-12-915-2021"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.1700578"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1785\/0120180080"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1029\/2017jb015251"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1093\/gji\/ggy423"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2020.07.025"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.earscirev.2006.07.004"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1785\/0120180130"},{"key":"ref16","first-page":"3257","article-title":"Training deep learning based denoisers without ground truth data","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Soltanayev"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01050"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1190\/geo2013-0382.1"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1785\/0220190028"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1190\/geo2018-0668.1"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2947149"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1190\/geo2019-0468.1"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2926772"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2783381"},{"key":"ref25","first-page":"524","article-title":"Noise2self: Blind denoising by self-supervision","volume-title":"Proc. 36th Int. Conf. Mach. Learn.","author":"Batson"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref27","article-title":"Making convolutional networks shift-invariant again","volume-title":"arXiv:1904.11486","author":"Zhang","year":"2019"},{"key":"ref28","article-title":"Searching for activation functions","volume-title":"arXiv:1710.05941","author":"Ramachandran","year":"2017"},{"key":"ref29","article-title":"Provable benefit of orthogonal initialization in optimizing deep linear networks","volume-title":"arXiv:2001.05992","author":"Hu","year":"2020"},{"key":"ref30","article-title":"Adam: A method for stochastic optimization","volume-title":"arXiv:1412.6980","author":"Kingma","year":"2014"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1029\/2020jb020925"},{"key":"ref32","volume-title":"Pi\u00f1on flats observatory array","year":"2014"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1093\/gji\/ggy102"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1785\/BSSA07206B0225"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1002\/9781119521808.ch9"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.7717\/peerj.453"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2019.8802964"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1111\/1365-2478.12324"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2008.4541250"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.2478\/s11600-010-0032-7"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1126\/science.aab0476"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1785\/0220180122"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1029\/GL014i001p00013"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1093\/gji\/ggy359"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1002\/2016gl069750"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1029\/2011GL048118"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1093\/gji\/ggz479"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2693418"},{"key":"ref49","article-title":"Relational inductive biases, deep learning, and graph networks","volume-title":"arXiv:1806.01261","author":"Battaglia","year":"2018"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1029\/2020GL088690"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1093\/gji\/ggab139"},{"key":"ref52","article-title":"TensorFlow: Large-scale machine learning on heterogeneous systems","volume-title":"arXiv:1603.04467","author":"Abadi","year":"2015"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2649-2"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-019-0686-2"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/MCSE.2007.55"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/10175014\/09655039.pdf?arnumber=9655039","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,10]],"date-time":"2024-01-10T00:35:25Z","timestamp":1704846925000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9655039\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7]]},"references-count":55,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2021.3132832","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7]]}}}