{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T23:36:58Z","timestamp":1771025818837,"version":"3.50.1"},"reference-count":21,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,7,2]],"date-time":"2023-07-02T00:00:00Z","timestamp":1688256000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,7,2]],"date-time":"2023-07-02T00:00:00Z","timestamp":1688256000000},"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":[[2023,7,2]]},"DOI":"10.1109\/ssp53291.2023.10207930","type":"proceedings-article","created":{"date-parts":[[2023,8,9]],"date-time":"2023-08-09T17:24:22Z","timestamp":1691601862000},"page":"695-699","source":"Crossref","is-referenced-by-count":10,"title":["Optimized preprocessing and Tiny ML for Attention State Classification"],"prefix":"10.1109","author":[{"given":"Yinghao","family":"Wang","sequence":"first","affiliation":[{"name":"Institut Polytechnique de Paris,LTCI, Télécom Paris"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R\u00e9mi","family":"Nahon","sequence":"additional","affiliation":[{"name":"Institut Polytechnique de Paris,LTCI, Télécom Paris"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enzo","family":"Tartaglione","sequence":"additional","affiliation":[{"name":"Institut Polytechnique de Paris,LTCI, Télécom Paris"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pavlo","family":"Mozharovskyi","sequence":"additional","affiliation":[{"name":"Institut Polytechnique de Paris,LTCI, Télécom Paris"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Van-Tam","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Institut Polytechnique de Paris,LTCI, Télécom Paris"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.91.16.7398"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/s130810273"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0046692"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2017.00051"},{"key":"ref5","volume-title":"Time-frequency signal analysis and processing: a comprehensive reference","author":"Boashash","year":"2015"},{"key":"ref6","volume-title":"Discrete-time signal processing","author":"Oppenheim","year":"1999"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.05.057"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1051\/matecconf\/201821403009"},{"key":"ref9","first-page":"178","article-title":"Learning robust features using deep learning for automatic seizure detection","volume-title":"Machine learning for healthcare conference","author":"Thodoroff"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s11571-020-09626-1"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-021-06038-y"},{"key":"ref12","first-page":"3","article-title":"The ten-twenty electrode system of the international federation. the international federation of clinical neurophysiology","volume":"52","author":"Klem","year":"1999","journal-title":"Electroencephalogr. Clin. Neurophysiol. Suppl."},{"key":"ref13","article-title":"Fifa: Making fairness more generalizable in classifiers trained on imbalanced data","author":"Deng","year":"2022"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3390\/app7020150"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ISSPA.2003.1224804"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.117417"},{"key":"ref17","article-title":"No unbiased estimator of the variance of k-fold cross-validation","volume":"16","author":"Bengio","year":"2003","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2018.05.116"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3497623.3497687"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967868"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3446776"}],"event":{"name":"2023 IEEE Statistical Signal Processing Workshop (SSP)","location":"Hanoi, Vietnam","start":{"date-parts":[[2023,7,2]]},"end":{"date-parts":[[2023,7,5]]}},"container-title":["2023 IEEE Statistical Signal Processing Workshop (SSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10207925\/10207926\/10207930.pdf?arnumber=10207930","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T17:54:38Z","timestamp":1709315678000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10207930\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,2]]},"references-count":21,"URL":"https:\/\/doi.org\/10.1109\/ssp53291.2023.10207930","relation":{},"subject":[],"published":{"date-parts":[[2023,7,2]]}}}