{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T15:59:42Z","timestamp":1730303982828,"version":"3.28.0"},"reference-count":67,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100008982","name":"Qatar National Research Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008982","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001321","name":"National Research Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001321","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1]]},"DOI":"10.1109\/wacv51458.2022.00138","type":"proceedings-article","created":{"date-parts":[[2022,2,15]],"date-time":"2022-02-15T20:56:28Z","timestamp":1644958588000},"page":"1311-1321","source":"Crossref","is-referenced-by-count":23,"title":["YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUs"],"prefix":"10.1109","author":[{"given":"Prakhar","family":"Ganesh","sequence":"first","affiliation":[{"name":"Advanced Digital Sciences Center,Singapore"}]},{"given":"Yao","family":"Chen","sequence":"additional","affiliation":[{"name":"Advanced Digital Sciences Center,Singapore"}]},{"given":"Yin","family":"Yang","sequence":"additional","affiliation":[{"name":"Hamad Bin Khalifa University,College of Science and Engineering,Qatar"}]},{"given":"Deming","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign,USA"}]},{"given":"Marianne","family":"Winslett","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign,USA"}]}],"member":"263","reference":[{"key":"ref39","first-page":"7263","article-title":"YOLO9000: better, faster, stronger","author":"redmon","year":"2017","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/WACV48630.2021.00191"},{"key":"ref33","first-page":"116","article-title":"Shufflenet v2:Practical guidelines for efficient cnn architecture design","author":"ma","year":"2018","journal-title":"Proceedings of the European Conference on Computer Vision (ECCV)"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-03243-2_798-1"},{"article-title":"Sgdr: Stochastic gradient descent with warm restarts","year":"2016","author":"loshchilov","key":"ref31"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00913"},{"article-title":"Yolo-fastest","year":"2020","author":"quiqui","key":"ref37"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00682"},{"key":"ref35","first-page":"483","article-title":"Stacked hourglass networks for human pose estimation","author":"newell","year":"2016","journal-title":"European Conference on Computer Vision"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2941547"},{"key":"ref60","first-page":"3320","article-title":"How transferable are features in deep neural networks?","volume":"27","author":"yosinski","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD.2017.8203862"},{"journal-title":"Conference on Machine Learning and Systems (MLSys)","article-title":"SkyNet: a hardware-efficient method for object detection and tracking on embedded systems","year":"2020","author":"zhang","key":"ref61"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00716"},{"key":"ref28","first-page":"740","article-title":"Microsoft COCO: Common objects in context","author":"lin","year":"2014","journal-title":"European Conference on Computer Vision"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.3390\/s20071861"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106"},{"key":"ref65","doi-asserted-by":"crossref","first-page":"9259","DOI":"10.1609\/aaai.v33i01.33019259","article-title":"M2det:A single-shot object detector based on multi-level feature pyramid network","volume":"33","author":"zhao","year":"2019","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6999"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01247-4"},{"key":"ref67","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/JPROC.2020.3004555","article-title":"A comprehensive survey on transfer learning","volume":"109","author":"zhuang","year":"2020","journal-title":"Proceedings of the IEEE"},{"article-title":"YOLOv4: Optimal speed and accuracy of object detection","year":"2020","author":"bochkovskiy","key":"ref2"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-09004-3"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-017-9582-2"},{"article-title":"Cornernet-lite: Efficient keypoint based object detection","year":"2019","author":"law","key":"ref22"},{"key":"ref21","first-page":"734","article-title":"Cornernet: Detecting objects as paired keypoints","author":"law","year":"2018","journal-title":"Proceedings of the European Conference on Computer Vision (ECCV)"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCIA49625.2020.00008"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-50516-5_7"},{"article-title":"Detnet: A backbone network for object detection","year":"2018","author":"li","key":"ref26"},{"article-title":"Tiny-DSOD: Lightweight object detection for resource-restricted usages","year":"2018","author":"li","key":"ref25"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9054101"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01283"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2020.102756"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1145\/3391743"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00382"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.60"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/EMC2-NIPS53020.2019.00013"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CRV.2018.00023"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00206"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00203"},{"key":"ref10","first-page":"1804","article-title":"Yolov3: An incremental improvement","author":"farhadi","year":"2018","journal-title":"Computer Vision and Pattern Recognition"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00720"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00075"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-13-7166-0_16"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00140"},{"article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","year":"2017","author":"howard","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8621865"},{"article-title":"Poly-YOLO: higher speed, more precise detection and instance segmentation for YOLOv3","year":"2020","author":"hurtik","key":"ref17"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9412795"},{"article-title":"Squeezenet: Alexnet-level accuracy with 50x fewer parameters and¡ 0.5 mb model size","year":"2016","author":"iandola","key":"ref19"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01362"},{"article-title":"A survey of modern object detection literature using deep learning","year":"2018","author":"chahal","key":"ref3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01161"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/WACV48630.2021.00360"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00667"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2961959"},{"key":"ref46","first-page":"23","article-title":"Self-driving cars: Evaluation of deep learning techniques for object detection in different driving conditions","volume":"2","author":"simhambhatla","year":"2019","journal-title":"SMU Data Science Review"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TBIOM.2019.2897807"},{"key":"ref48","first-page":"6105","article-title":"EfficientNet: Rethinking model scaling for convolutional neural networks","author":"tan","year":"2019","journal-title":"International Conference on Machine Learning"},{"key":"ref47","first-page":"2820","article-title":"Mnas-net: Platform-aware neural architecture search for mobile","author":"tan","year":"2019","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref44","article-title":"Survey of mobile robot vision self-localization","volume":"7","author":"shang","year":"2019","journal-title":"Journal of Automation and Control Engineering VOL"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.15353\/vsnl.v3i1.171"}],"event":{"name":"2022 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV)","start":{"date-parts":[[2022,1,3]]},"location":"Waikoloa, HI, USA","end":{"date-parts":[[2022,1,8]]}},"container-title":["2022 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9706406\/9706408\/09706815.pdf?arnumber=9706815","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,9]],"date-time":"2022-06-09T21:24:27Z","timestamp":1654809867000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9706815\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1]]},"references-count":67,"URL":"http:\/\/dx.doi.org\/10.1109\/wacv51458.2022.00138","relation":{},"subject":[],"published":{"date-parts":[[2022,1]]}}}