{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T09:14:46Z","timestamp":1781082886367,"version":"3.54.1"},"reference-count":53,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["61203237"],"award-info":[{"award-number":["61203237"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Industry-Academia Cooperation Innovation Fund Projection of Jiangsu Province","award":["BY2016001-02"],"award-info":[{"award-number":["BY2016001-02"]}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20191371"],"award-info":[{"award-number":["BK20191371"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Instrum. Meas."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tim.2021.3102735","type":"journal-article","created":{"date-parts":[[2021,8,5]],"date-time":"2021-08-05T19:52:37Z","timestamp":1628193157000},"page":"1-13","source":"Crossref","is-referenced-by-count":71,"title":["Deep Neural Networks for Sensor-Based Human Activity Recognition Using Selective Kernel Convolution"],"prefix":"10.1109","volume":"70","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2314-9735","authenticated-orcid":false,"given":"Wenbin","family":"Gao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8749-7459","authenticated-orcid":false,"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6664-1172","authenticated-orcid":false,"given":"Wenbo","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7826-3124","authenticated-orcid":false,"given":"Fuhong","family":"Min","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1671-2283","authenticated-orcid":false,"given":"Jun","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1982-6780","authenticated-orcid":false,"given":"Aiguo","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","first-page":"630","article-title":"Identity mappings in deep residual networks","author":"he","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref38","article-title":"Highway networks","author":"kumar srivastava","year":"2015","journal-title":"arXiv 1505 00387"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2016.01.001"},{"key":"ref32","first-page":"8","article-title":"Deep activity recognition models with triaxial accelerometers","author":"alsheikh","year":"2016","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3267242.3267286"},{"key":"ref30","first-page":"915","article-title":"Real-time human activity recognition from accelerometer data using convolutional neural networks","volume":"62","author":"andrey","year":"2017","journal-title":"Appl Soft Comput"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2019.03.068"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1038\/11197"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/0006-8993(78)90937-X"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.1962.sp006837"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.04.032"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.3015521"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3390\/info10060203"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.08.096"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2018.02.010"},{"key":"ref20","article-title":"Deep, convolutional, and recurrent models for human activity recognition using wearables","author":"hammerla","year":"2016","journal-title":"arXiv 1604 08880"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.3390\/s16010115"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2806333"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/779"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.01.025"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3390\/s18020679"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.2978772"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref52","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00060"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01104"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00919"},{"key":"ref12","first-page":"3","article-title":"A public domain dataset for human activity recognition using smartphones","volume":"3","author":"anguita","year":"2013","journal-title":"Proc ESANN"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3390\/app7101101"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/1964897.1964918"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ISWC.2012.13"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2012.12.014"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.4108\/icst.mobicase.2014.257786"},{"key":"ref18","first-page":"3995","article-title":"Deep convolutional neural networks on multichannel time series for human activity recognition","volume":"15","author":"yang","year":"2015","journal-title":"Proc IJCAI"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2019.2917225"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2019.2895931"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2020.3003395"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.cogsys.2018.11.009"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2019.2945467"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref49","article-title":"Network in network","author":"lin","year":"2013","journal-title":"arXiv 1312 4400"},{"key":"ref9","first-page":"4278","article-title":"Inception-V4, inception-resnet and the impact of residual connections on learning","volume":"31","author":"szegedy","year":"2017","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref46","first-page":"315","article-title":"Deep sparse rectifier neural networks","author":"glorot","year":"2011","journal-title":"Proc 14th Int Conf Artif Intell Statist"},{"key":"ref45","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00759"},{"key":"ref47","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","volume":"25","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2787612"},{"key":"ref41","first-page":"667","article-title":"Dynamic filter networks","author":"jia","year":"2016","journal-title":"Proc NIPS"},{"key":"ref44","first-page":"2990","article-title":"Group equivariant convolutional networks","author":"cohen","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref43","article-title":"Pay less attention with lightweight and dynamic convolutions","author":"wu","year":"2019","journal-title":"arXiv 1901 10430"}],"container-title":["IEEE Transactions on Instrumentation and Measurement"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/19\/9259274\/09507456.pdf?arnumber=9507456","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:51:35Z","timestamp":1652194295000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9507456\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":53,"URL":"https:\/\/doi.org\/10.1109\/tim.2021.3102735","relation":{},"ISSN":["0018-9456","1557-9662"],"issn-type":[{"value":"0018-9456","type":"print"},{"value":"1557-9662","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}