{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T15:56:47Z","timestamp":1762876607779,"version":"3.37.0"},"reference-count":32,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T00:00:00Z","timestamp":1725667200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T00:00:00Z","timestamp":1725667200000},"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":[[2024,9,7]]},"DOI":"10.1109\/aibthings63359.2024.10861885","type":"proceedings-article","created":{"date-parts":[[2025,2,7]],"date-time":"2025-02-07T18:38:03Z","timestamp":1738953483000},"page":"1-5","source":"Crossref","is-referenced-by-count":2,"title":["Real-Time Drivers\u2019 Drowsiness Detection: A Deep Learning Approach"],"prefix":"10.1109","author":[{"given":"Ank","family":"Zaman","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prosenjit","family":"Chatterjee","sequence":"additional","affiliation":[{"name":"Southern Utah University,Dept of Computer Science & Cyber Security,Ceder City,UT,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rajat","family":"Sharma","sequence":"additional","affiliation":[{"name":"Wilfrid Laurier University,Dept of Physics & Computer Science,Waterloo,ON,Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Prevalence of drowsy driving crashes: Estimates from a large-scale naturalistic driving study","author":"Foundation","year":"2023","journal-title":"AAA Foundation for Traffic Safety"},{"year":"2024","key":"ref2","article-title":"National highway traffic safety administration"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"100864","DOI":"10.1016\/j.trip.2023.100864","article-title":"A systematic review on detection and prediction of driver drowsiness","volume":"21","author":"Ebrahim Shaik","year":"2023","journal-title":"Transportation Research Interdisciplinary Perspectives"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3390\/s23218741"},{"key":"ref5","first-page":"368","article-title":"Driver drowsiness detection system based on eeg signal","volume-title":"2019 6th International Conference on Computing for Sustainable Global Development (INDIACom)","author":"Kaur"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"103583","DOI":"10.1016\/j.cviu.2022.103583","article-title":"Periocular biometrics and its relevance to partially masked faces: A survey","volume":"226","author":"Sharma","year":"2023","journal-title":"Computer Vision and Image Understanding"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2023.3301060"},{"year":"2024","key":"ref8","article-title":"Convolutional neural network (cnn) - tensorflow core"},{"year":"2015","key":"ref9","article-title":"Open source computer vision library"},{"key":"ref10","first-page":"179","article-title":"Driver drowsiness detection system using cnn-based deep learning","volume-title":"2021 International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS)","author":"Chakraborty"},{"year":"2024","key":"ref11","article-title":"Cvlab at national tsing hua university"},{"year":"2023","key":"ref12","article-title":"Yawn-eye dataset (new)"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3423723"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3333252"},{"key":"ref15","first-page":"1","article-title":"Real-time driver drowsiness detection system based on convolutional neural network and attention mechanism","volume":"2021","author":"Zhao","year":"2021","journal-title":"Journal of Advanced Transportation"},{"key":"ref16","first-page":"714","article-title":"Driver drowsiness detection using cnn and svm on opencv","volume-title":"2020 5th International Conference on Computing Communication and Automation (ICCCA)","author":"Kumar"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3381999"},{"article-title":"Fer-2013","year":"2023","author":"Msambare","key":"ref18"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3110813"},{"key":"ref20","first-page":"3333","article-title":"Driver drowsiness detection system based on improved cnn algorithm","author":"Zhang","year":"2021"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-3383-9_19"},{"key":"ref22","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-54526-4_9","article-title":"Driver drowsiness detection via a hierarchical temporal deep belief network","volume-title":"ACCV Workshops","author":"Weng"},{"key":"ref23","first-page":"1","article-title":"Driver drowsiness detection system using convolutional neural network and opencv libraries","author":"Pandey","year":"2020"},{"key":"ref24","first-page":"471","article-title":"Driver drowsiness detection based on cnn algorithm","volume-title":"2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE)","author":"Chen"},{"key":"ref25","first-page":"1405","article-title":"Real-time driver drowsiness detection using convolutional neural network and opencv","volume-title":"2020 International Conference on Electronics and Sustainable Communication Systems (ICESC)","author":"Mukherjee"},{"year":"2024","key":"ref26","article-title":"Driver-drowsiness github repository"},{"issue":"3","key":"ref27","doi-asserted-by":"crossref","DOI":"10.3390\/jimaging6030008","article-title":"Real-time system for driver fatigue detection based on a recurrent neuronal network","volume":"6","author":"Ed-Doughmi","year":"2020","journal-title":"Journal of Imaging"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-05209-7"},{"key":"ref29","doi-asserted-by":"crossref","DOI":"10.14569\/IJACSA.2020.0111043","article-title":"Robust drowsiness detection for vehicle driver using deep convolutional neural network","volume":"11","author":"Saif","year":"2020","journal-title":"International Journal of Advanced Computer Science and Applications"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"106107","DOI":"10.1016\/j.aap.2021.106107","article-title":"Using long short term memory and convolutional neural networks for driver drowsiness detection","volume":"156","author":"Quddus","year":"2021","journal-title":"Accident Analysis & Prevention"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04506-0"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3288008"}],"event":{"name":"2024 IEEE 2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings)","start":{"date-parts":[[2024,9,7]]},"location":"Mt Pleasant, MI, USA","end":{"date-parts":[[2024,9,8]]}},"container-title":["2024 2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10860733\/10861884\/10861885.pdf?arnumber=10861885","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,8]],"date-time":"2025-02-08T05:36:25Z","timestamp":1738992985000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10861885\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,7]]},"references-count":32,"URL":"https:\/\/doi.org\/10.1109\/aibthings63359.2024.10861885","relation":{},"subject":[],"published":{"date-parts":[[2024,9,7]]}}}