{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T21:49:07Z","timestamp":1776289747790,"version":"3.50.1"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T00:00:00Z","timestamp":1662595200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T00:00:00Z","timestamp":1662595200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1007\/s11042-022-13697-z","type":"journal-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T15:08:26Z","timestamp":1662649706000},"page":"13241-13273","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["AI-based face mask detection system: a straightforward proposition to fight with Covid-19 situation"],"prefix":"10.1007","volume":"82","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1289-2160","authenticated-orcid":false,"given":"Ruchi","family":"Jayaswal","sequence":"first","affiliation":[]},{"given":"Manish","family":"Dixit","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,9,8]]},"reference":[{"issue":"6","key":"13697_CR1","doi-asserted-by":"publisher","first-page":"8759","DOI":"10.1007\/s11042-020-10103-4","volume":"80","author":"M Ansari","year":"2021","unstructured":"Ansari M, Singh DK (2021) Human detection techniques for real time surveillance: A comprehensive survey. Multimed Tools Appl 80(6):8759\u20138808","journal-title":"Multimed Tools Appl"},{"issue":"3\u20134","key":"13697_CR2","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1002\/cav.38","volume":"15","author":"A Bastanfard","year":"2004","unstructured":"Bastanfard A, Bastanfard O, Takahashi H, Nakajima M (2004) Toward anthropometrics simulation of face rejuvenation and skin cosmetic. Comput Animation Virt Worlds 15(3\u20134):347\u2013352","journal-title":"Comput Animation Virt Worlds"},{"key":"13697_CR3","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1109\/CW.2004.65","volume-title":"2004 International conference on Cyberworlds","author":"A Bastanfard","year":"2004","unstructured":"Bastanfard A, Takahashi H, Nakajima M (2004) Toward E-appearance of human face and hair by age, expression and rejuvenation. In: 2004 International conference on Cyberworlds. IEEE, pp 306\u2013311"},{"key":"13697_CR4","doi-asserted-by":"publisher","unstructured":"Bazi Y, Al Rahhal MM, Alhichri H, Alajlan N (2019) Simple yet effective fine-tuning of deep CNNs using an auxiliary classification loss for remote sensing scene classification. Remote Sens 11(24):2908. https:\/\/doi.org\/10.3390\/rs11242908","DOI":"10.3390\/rs11242908"},{"key":"13697_CR5","doi-asserted-by":"publisher","unstructured":"Chollet F (2017)\u00a0Xception: deep learning with depthwise separable convolutions. In:\u00a02017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp\u00a01800-1807. https:\/\/doi.org\/10.1109\/CVPR.2017.195","DOI":"10.1109\/CVPR.2017.195"},{"key":"13697_CR6","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/978-3-030-66665-1_6","volume-title":"International Conference on Big Data Analytics","author":"GJ Chowdary","year":"2020","unstructured":"Chowdary GJ, Punn NS, Sonbhadra SK, Agarwal S (2020) Face mask detection using transfer learning of inceptionv3. In: International Conference on Big Data Analytics. Springer, Cham, pp 81\u201390"},{"issue":"1","key":"13697_CR7","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1037\/0096-3445.136.1.23","volume":"136","author":"T Dalgleish","year":"2007","unstructured":"Dalgleish T, Williams JMG, Golden AMJ, Perkins N, Barrett LF, Barnard PJ, Au Yeung C, Murphy V, Elward R, Tchanturia K, Watkins E (2007) Reduced Specifity of autographical memory and depression. J Exp Psychol Gen 136(1):23\u201342","journal-title":"J Exp Psychol Gen"},{"key":"13697_CR8","first-page":"1","volume-title":"2020 IEEE 17th India Council International Conference (INDICON)","author":"A Das","year":"2020","unstructured":"Das A, Ansari MW, Basak R (2020) Covid-19 face mask detection using TensorFlow, Keras and OpenCV. In: 2020 IEEE 17th India Council International Conference (INDICON). IEEE, pp 1\u20135"},{"key":"13697_CR9","doi-asserted-by":"crossref","unstructured":"Deng J, Guo J, Zhou Y et al (2019) Retinaface: Single-stage dense face localisation in the wild. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp 5203\u20135212","DOI":"10.1109\/CVPR42600.2020.00525"},{"key":"13697_CR10","first-page":"4077","volume-title":"2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)","author":"Y Duan","year":"2016","unstructured":"Duan Y, Zhou L, Wu Y (2016) Facial Expression Recognition Based on Convolution Neural Network. In: 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017). Atlantis press, pp 4077\u20134081 Jul 13"},{"key":"13697_CR11","doi-asserted-by":"publisher","unstructured":"Duchi JC, Bartlett PL, Wainwright MJ (2012) Randomized smoothing for (parallel) stochastic optimization. In:\u00a02012 IEEE 51st IEEE Conference on Decision and Control (CDC), pp 5442\u20135444. https:\/\/doi.org\/10.1109\/CDC.2012.6426698","DOI":"10.1109\/CDC.2012.6426698"},{"key":"13697_CR12","doi-asserted-by":"publisher","unstructured":"Ge S, Li J, Ye Q, Luo Z (2017) Detecting masked faces in the wild with LLE-CNNs. In:\u00a02017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),\u00a0pp 426\u2013434. https:\/\/doi.org\/10.1109\/CVPR.2017.53","DOI":"10.1109\/CVPR.2017.53"},{"key":"13697_CR13","doi-asserted-by":"crossref","unstructured":"Guo Y, Shi H, Kumar A, Grauman K, Simunic T, Feris RS (2019) SpotTune: transfer learning through adaptive fine-tuning. In:\u00a02019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp 4800\u20134809","DOI":"10.1109\/CVPR.2019.00494"},{"issue":"3","key":"13697_CR14","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1007\/s00371-020-01814-8","volume":"37","author":"S Gupta","year":"2021","unstructured":"Gupta S, Thakur K, Kumar M (2021) 2D-human face recognition using SIFT and SURF descriptors of face\u2019s feature regions. Vis Comput 37(3):447\u2013456","journal-title":"Vis Comput"},{"key":"13697_CR15","doi-asserted-by":"crossref","unstructured":"Hariri W (2021) Efficient masked face recognition method during the covid-19 pandemic. SIViP:1\u20138","DOI":"10.21203\/rs.3.rs-39289\/v4"},{"key":"13697_CR16","doi-asserted-by":"crossref","unstructured":"Hussain, GKJ,\u00a0Priya R, Rajarajeswari S, Prasanth P, Niyazuddeen N\u00a0(2021) The face mask detection technology for Image analysis in the covid-19 surveillance system. J Phys Conf Ser\u00a01916(1):012084. IOP Publishing","DOI":"10.1088\/1742-6596\/1916\/1\/012084"},{"key":"13697_CR17","doi-asserted-by":"crossref","unstructured":"Jayaswal R, Dixit M (2020) Comparative analysis of human face recognition by traditional methods and deep learning in real-time environment. In:\u00a02020 IEEE 9th International Conference on Communication Systems and Network Technologies (CSNT). IEEE, pp 66\u201371","DOI":"10.1109\/CSNT48778.2020.9115779"},{"issue":"6","key":"13697_CR18","doi-asserted-by":"publisher","first-page":"1875","DOI":"10.18280\/ts.380632","volume":"38","author":"R Jayaswal","year":"2021","unstructured":"Jayaswal R, Dixit M (2021) Detection of hidden facial surface masking in stored and real time captured images: a deep learning perspective in Covid time. Traitem du Sig 38(6):1875\u20131885","journal-title":"Traitem du Sig"},{"key":"13697_CR19","doi-asserted-by":"crossref","unstructured":"Jayaswal R, Jha J (2017) A hybrid approach for image retrieval using visual descriptors. In:\u00a02017 International Conference on Computing, Communication and Automation (ICCCA). IEEE,\u00a0pp 1125\u20131130","DOI":"10.1109\/CCAA.2017.8229965"},{"key":"13697_CR20","unstructured":"Jiang M, Fan X (2020) RetinaMask: A Face Mask detector. arXiv preprint arXiv:2005.03950."},{"key":"13697_CR21","unstructured":"Kingma DP, Ba J (2014) Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"issue":"16","key":"13697_CR22","doi-asserted-by":"publisher","first-page":"21557","DOI":"10.1007\/s11042-017-5587-8","volume":"77","author":"M Kumar","year":"2018","unstructured":"Kumar M, Chhabra P, Garg NK (2018) An efficient content based image retrieval system using BayesNet and K-NN. Multimed Tools Appl 77(16):21557\u201321570","journal-title":"Multimed Tools Appl"},{"issue":"2","key":"13697_CR23","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1007\/s10462-018-9650-2","volume":"52","author":"A Kumar","year":"2019","unstructured":"Kumar A, Kaur A, Kumar M (2019) Face detection techniques: a review. Artif Intell Rev 52(2):927\u2013948","journal-title":"Artif Intell Rev"},{"key":"13697_CR24","doi-asserted-by":"crossref","unstructured":"Mahan HB, Holt G, Sculley D, Young M, Ebner D, Grady J, Nie L et al (2013) Ad click prediction: a view from the trenches. In: Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, pp 1222\u20131230","DOI":"10.1145\/2487575.2488200"},{"key":"13697_CR25","doi-asserted-by":"publisher","first-page":"102692","DOI":"10.1016\/j.scs.2020.102692","volume":"66","author":"P Nagrath","year":"2021","unstructured":"Nagrath P, Jain R, Madan A, Arora R, Kataria P, Hemanth J (2021) SSDMNV2: a real time DNN-based face mask detection system using single shot multibox detector and MobileNetV2. Sustain Cities Soc 66:102692","journal-title":"Sustain Cities Soc"},{"key":"13697_CR26","unstructured":"Paul S, Kurin V, Whiteson S (2019) Fast efficient hyperparameter tuning for policy gradient methods. Advances in Neural Information Processing Systems 32"},{"issue":"53","key":"13697_CR27","first-page":"1","volume":"20","author":"P Probst","year":"2019","unstructured":"Probst P, Boulesteix AL, Bischl B (2019) Tunability: importance of Hyperparameters of machine learning algorithms. J Mach Learn Res 20(53):1\u201332","journal-title":"J Mach Learn Res"},{"key":"13697_CR28","unstructured":"Ruder S (2016) An overview of gradient descent optimization algorithms. arXiv preprint arXiv:1609.04747"},{"key":"13697_CR29","doi-asserted-by":"crossref","unstructured":"Sandler M, Howard A, Zhu M, Zhmoginov A, et al. (2018). Mobilenetv2: inverted residuals and linear bottlenecks. In proceedings of the IEEE conference on computer vision and pattern recognition: 4510-20.","DOI":"10.1109\/CVPR.2018.00474"},{"key":"13697_CR30","doi-asserted-by":"publisher","first-page":"103848","DOI":"10.1016\/j.jbi.2021.103848","volume":"120","author":"S Sethi","year":"2021","unstructured":"Sethi S, Kathuria M, Kaushik T (2021) Face mask detection using deep learning: an approach to reduce risk of coronavirus spread. J Biomed Inform 120:103848","journal-title":"J Biomed Inform"},{"key":"13697_CR31","unstructured":"Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556:1\u201314"},{"issue":"13","key":"13697_CR32","doi-asserted-by":"publisher","first-page":"19753","DOI":"10.1007\/s11042-021-10711-8","volume":"80","author":"S Singh","year":"2021","unstructured":"Singh S, Ahuja U, Kumar M, Kumar K, Sachdeva M (2021) Face mask detection using YOLOv3 and faster R-CNN models: COVID-19 environment. Multimed Tools Appl 80(13):19753\u201319768","journal-title":"Multimed Tools Appl"},{"key":"13697_CR33","first-page":"1","volume-title":"2020 3rd International Conference on Applied Engineering (ICAE)","author":"S Susanto","year":"2020","unstructured":"Susanto S, Putra FA, Analia R, Suciningtyas IKLN (2020) The Face Mask Detection For Preventing the Spread of COVID-19 at Politeknik Negeri Batam. In: 2020 3rd International Conference on Applied Engineering (ICAE). IEEE, pp 1\u20135"},{"key":"13697_CR34","unstructured":"Sutskever I, Martens J, Dahl G, Hinton G\u00a0(2013) On the importance of initialization and momentum in deep learning. In: International conference on machine learning. PMLR, pp 1139\u20131147"},{"key":"13697_CR35","doi-asserted-by":"crossref","unstructured":"Szegedy C, Vanhoucke V, Ioffe S, Shlens J, Wojna Z (2016) Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2818\u20132826","DOI":"10.1109\/CVPR.2016.308"},{"key":"13697_CR36","unstructured":"W. H. O.organization, Coronavirus disease (COVID-19) Situation Report (2020) https:\/\/www.who.int\/emergencies\/diseases\/novel-coronavirus-2019\/situation-reports\/. Accessed June 10, 2020."},{"key":"13697_CR37","unstructured":"Wang Z, Xiong Z, Hong Q et al (2020) Masked face recognition dataset and application. arXiv preprint arXiv:2003.09093"},{"key":"13697_CR38","unstructured":"World Health Organization, Coronavirus disease (COVID-19) advice for the public (2020) https:\/\/www.who.int\/emergencies\/diseases\/novel-coronavirus-2019\/advice-for-public. Accessed June 10, 2020."},{"key":"13697_CR39","unstructured":"Worldometer, COVID-19 Coronavirus Pandemic, (2020) https:\/\/www.worldometers.info\/corona-virus\/. Accessed June 10, 2020."},{"issue":"7","key":"13697_CR40","doi-asserted-by":"publisher","first-page":"1368","DOI":"10.22214\/ijraset.2020.30560","volume":"8","author":"S Yadav","year":"2020","unstructured":"Yadav S (2020) Deep learning based safe social distancing and face mask detection in public areas for covid-19 safety guidelines adherence. Int J Res Appl Sci Engin Technol 8(7):1368\u20131375","journal-title":"Int J Res Appl Sci Engin Technol"},{"key":"13697_CR41","doi-asserted-by":"publisher","unstructured":"Zegedy C et al (2015) Going deeper with convolutions. In:\u00a02015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp 1\u20139. https:\/\/doi.org\/10.1109\/CVPR.2015.7298594","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"13697_CR42","unstructured":"Zeiler MD (2012) Adadelta: an adaptive learning rate method. arXiv preprint arXiv:1212.5701"},{"key":"13697_CR43","unstructured":"Zhang F, Fan X, Ai G et al\u00a0(2019). Accurate face detection for high performance. arXiv preprint arXiv:1905.01585:1\u20139"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13697-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-13697-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13697-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,21]],"date-time":"2023-03-21T10:21:04Z","timestamp":1679394064000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-13697-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,8]]},"references-count":43,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["13697"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-13697-z","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,8]]},"assertion":[{"value":"30 May 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 March 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 August 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 September 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"None of the authors of this paper have a financial or personal relationship with other people or organizations that could inappropriately influence or bias the content of the paper. It is to specifically state that \u201cNo Competing interests are at stake and there is No Conflict of Interest\u201d with other people or organizations that could inappropriately influence or bias the content of the paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}