{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T03:49:27Z","timestamp":1792813767271,"version":"4.5.0"},"reference-count":70,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/access.2022.3214214","type":"journal-article","created":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T19:34:06Z","timestamp":1665689646000},"page":"109167-109186","source":"Crossref","is-referenced-by-count":28,"title":["Anatomy of Deep Learning Image Classification and Object Detection on Commercial Edge Devices: A Case Study on Face Mask Detection"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2116-785X","authenticated-orcid":false,"given":"Dimitrios","family":"Kolosov","sequence":"first","affiliation":[{"name":"School of Physics, Engineering and Computer Science, University of Hertfordshire, Hatfield, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vasilios","family":"Kelefouras","sequence":"additional","affiliation":[{"name":"School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3392-670X","authenticated-orcid":false,"given":"Pandelis","family":"Kourtessis","sequence":"additional","affiliation":[{"name":"School of Physics, Engineering and Computer Science, University of Hertfordshire, Hatfield, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6984-0268","authenticated-orcid":false,"given":"Iosif","family":"Mporas","sequence":"additional","affiliation":[{"name":"School of Physics, Engineering and Computer Science, University of Hertfordshire, Hatfield, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2019.00182"},{"key":"ref3","volume-title":"The Big Benchmarking Roundup","author":"Allan","year":"2022"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/csci46756.2018.00177"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/AVSS.2019.8909826"},{"key":"ref6","article-title":"Efficient execution of quantized deep learning models: A compiler approach","author":"Jain","year":"2020","journal-title":"arXiv:2006.10226"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-50420-5_34"},{"key":"ref8","article-title":"A survey of quantization methods for efficient neural network inference","author":"Gholami","year":"2021","journal-title":"arXiv:2103.13630"},{"key":"ref9","article-title":"EfficientNet: Rethinking model scaling for convolutional neural networks","author":"Tan","year":"2019","journal-title":"arXiv:1905.11946"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2022.103514"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"ref12","article-title":"You only look once: Unified, real-time object detection","author":"Redmon","year":"2015","journal-title":"arXiv:1506.02640"},{"key":"ref13","article-title":"Feature pyramid networks for object detection","author":"Lin","year":"2016","journal-title":"arXiv:1612.03144"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3363347.3363363"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2019.2930577"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICIST52614.2021.9440554"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3090196"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/IISWC47752.2019.9041955"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2020.101896"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/MDAT.2021.3095215"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICIMU49871.2020.9243367"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1587\/transinf.2020EDP7160"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/access.2019.2939201"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1134\/S1054661816010065"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPSW50202.2020.00152"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ISCON47742.2019.9036216"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58285-2_29"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.3390\/s19153371"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CSNT48778.2020.9115770"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPSW52791.2021.00128"},{"key":"ref33","first-page":"1","article-title":"Tensorflow lite micro: Embedded machine learning on TinyML systems","volume-title":"Proc. Mach. Learn. Syst.","author":"David"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICM46511.2021.9385682"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2020.102600"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/IEMTRONICS51293.2020.9216386"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/I2CT51068.2021.9418207"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3051844"},{"key":"ref39","volume-title":"Implementing a Real-Time, Ai-Based, Face Mask Detector Application for COVID-19","year":"2022"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref41","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017","journal-title":"arXiv:1704.04861"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00140"},{"key":"ref44","volume-title":"Tf.keras.Applications.Mobilenetv3large"},{"key":"ref45","volume-title":"Introducing the Next Generation of on-Device Vision Models: MobileNetv3 and Mobilenetedgetpu","author":"Howard","year":"2019"},{"key":"ref46","article-title":"Rethinking the inception architecture for computer vision","author":"Szegedy","year":"2015","journal-title":"arXiv:1512.00567"},{"key":"ref47","volume-title":"Tensorflow 1 Detection Model Zoo","year":"2022"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4842-6666-3_1"},{"key":"ref49","volume-title":"Faster Quantized Inference With XNNPACK","author":"Dukhan","year":"2021"},{"key":"ref50","volume-title":"EIQ Machine Learning Software Development Environment","year":"2022"},{"key":"ref51","volume-title":"Nxp Enables a Deeper View to Machine Learning","author":"Semiconductor"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00104"},{"key":"ref53","volume-title":"Accelerating Inference in Tf-Trt User Guide","year":"2022"},{"key":"ref54","volume-title":"Nvidia Tensorrt"},{"key":"ref55","volume-title":"Face Detector: Dataset","author":"Bhandary","year":"2022"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.30534\/ijatcse\/2021\/051032021"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.22214\/ijraset.2022.42947"},{"key":"ref58","article-title":"FDDB: A benchmark for face detection in unconstrained settings","author":"Jain","year":"2010"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2005.10.010"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"issue":"11","key":"ref61","first-page":"120","article-title":"The OpenCV library","volume":"25","author":"Bradski","year":"2000","journal-title":"Dr. Dobb\u2019s J. Softw. Tools"},{"key":"ref62","volume-title":"Pyturbojpeg","author":"Huang","year":"2022"},{"key":"ref63","volume-title":"Python Imaging Library","year":"2022"},{"key":"ref64","volume-title":"Pillow-SIMD","year":"2022"},{"key":"ref65","volume-title":"Flatbuffers","year":"2022"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2019.01289"},{"key":"ref67","volume-title":"Edge TPU Performance Benchmarks","year":"2022"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00215"},{"key":"ref69","volume-title":"Extremely Long Time to Load TRT-Optimized Frozen TF Graphs","year":"2022"},{"key":"ref70","volume-title":"Tensorflow\/Tensorrt (TF-TRT) Revisited","author":"Jung","year":"2022"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9668973\/09918067.pdf?arnumber=9918067","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T02:10:38Z","timestamp":1733883038000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9918067\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":70,"URL":"https:\/\/doi.org\/10.1109\/access.2022.3214214","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}