{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T16:43:45Z","timestamp":1761324225599,"version":"3.44.0"},"reference-count":75,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61672286"],"award-info":[{"award-number":["61672286"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2019,10]]},"DOI":"10.1109\/tits.2019.2921325","type":"journal-article","created":{"date-parts":[[2019,6,21]],"date-time":"2019-06-21T15:51:45Z","timestamp":1561132305000},"page":"3818-3831","source":"Crossref","is-referenced-by-count":24,"title":["Driver Pose Estimation Using Recurrent Lightweight Network and Virtual Data Augmented Transfer Learning"],"prefix":"10.1109","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0631-2385","authenticated-orcid":false,"given":"Yazhou","family":"Liu","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"}]},{"given":"Pongsak","family":"Lasang","sequence":"additional","affiliation":[{"name":"Panasonic Research and Development Center Singapore, Singapore"}]},{"given":"Sugiri","family":"Pranata","sequence":"additional","affiliation":[{"name":"Panasonic Research and Development Center Singapore, Singapore"}]},{"given":"Shengmei","family":"Shen","sequence":"additional","affiliation":[{"name":"Panasonic Research and Development Center Singapore, Singapore"}]},{"given":"Wenchao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Panasonic Research and Development Center Singapore, Singapore"}]}],"member":"263","reference":[{"key":"ref73","first-page":"2017","article-title":"Spatial transformer networks","author":"jaderberg","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref72","first-page":"807","article-title":"Rectified linear units improve restricted Boltzmann machines","author":"nair","year":"2010","journal-title":"Proc 27th Int Conf Int Conf Mach Learn"},{"key":"ref71","first-page":"4278","article-title":"Inception-v4, inception-ResNet and the impact of residual connections on learning","author":"szegedy","year":"2016","journal-title":"Proc 31st Nat Conf Artif Intell"},{"key":"ref70","first-page":"2148","article-title":"Predicting parameters in deep learning","author":"denil","year":"2013","journal-title":"Proc Neural Inf Process Syst"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995607"},{"key":"ref39","first-page":"1269","article-title":"Exploiting linear structure within convolutional networks for efficient evaluation","author":"denton","year":"2014","journal-title":"Proc Neural Inf Process Syst"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.471"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.690"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.597"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.137"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2762010"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.222"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.601"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.510"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.144"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref62","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref63","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2015","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10605-2_3"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.83"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref66","first-page":"21","article-title":"SSD: Single shot multibox detector","author":"liu","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref29","first-page":"1799","article-title":"Joint training of a convolutional network and a graphical model for human pose estimation","author":"tompson","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref68","first-page":"2377","article-title":"Training very deep networks","author":"srivastava","year":"2015","journal-title":"Proc Neural Inf Process Syst"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.298"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2017.2769096"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.583"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298629"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000042934.15159.49"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2015.06.013"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206754"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/T-C.1973.223602"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2318702"},{"key":"ref25","first-page":"1129","article-title":"Learning to parse images of articulated bodies","author":"ramanan","year":"2007","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-88688-4_6"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000029666.37597.d3"},{"key":"ref59","article-title":"Semantic image segmentation with deep convolutional nets and fully connected CRFs","author":"chen","year":"2015","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2781233"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10599-4_7"},{"key":"ref56","first-page":"ii-342","article-title":"Head pose estimation by non-linear embedding and mapping","author":"hu","year":"2005","journal-title":"Proc IEEE Int Conf Image Process"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2007.383280"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.106"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.446"},{"key":"ref52","article-title":"Face alignment by local deep descriptor regression","author":"kumar","year":"2016","journal-title":"arXiv 1601 07950"},{"key":"ref10","first-page":"593","article-title":"Learning hierarchical feature representation in depth image","author":"liu","year":"2014","journal-title":"Proc Asian Conf Comput Vis"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.214"},{"key":"ref40","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","author":"han","year":"2015","journal-title":"Proc Neural Inf Process Syst"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2017.141"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2014.2303296"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/2567948.2577348"},{"key":"ref15","first-page":"483","article-title":"Stacked hourglass networks for human pose estimation","author":"newell","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.511"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5540218"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.492"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.163"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.143"},{"key":"ref3","first-page":"1503","article-title":"Embedded recurrent network for head pose estimation in car","author":"guido","year":"2017","journal-title":"Proc IEEE Intell Vehicles Symp"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ISSCS.2015.7203942"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.261"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2398356.2398381"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126270"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1006\/cviu.1995.1004"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2014.2378019"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.239"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298882"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.75"},{"key":"ref42","article-title":"SqueezeNet: AlexNet-level accuracy with 50\n$\\times $\n fewer parameters and <0.5 MB model size","author":"iandola","year":"2017","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref41","article-title":"Deep Compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding","author":"han","year":"2016","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00716"},{"key":"ref43","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"howard","year":"2017","journal-title":"Proc Comput Vis Pattern Recognit"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/8855041\/08743560.pdf?arnumber=8743560","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T18:17:26Z","timestamp":1755627446000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8743560\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10]]},"references-count":75,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tits.2019.2921325","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"type":"print","value":"1524-9050"},{"type":"electronic","value":"1558-0016"}],"subject":[],"published":{"date-parts":[[2019,10]]}}}