{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T02:53:03Z","timestamp":1775875983469,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789811980688","type":"print"},{"value":"9789811980695","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-981-19-8069-5_38","type":"book-chapter","created":{"date-parts":[[2022,11,19]],"date-time":"2022-11-19T10:07:42Z","timestamp":1668852462000},"page":"560-573","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Face Recognition Based on\u00a0Deep Learning and\u00a0Data Augmentation"],"prefix":"10.1007","author":[{"given":"Lam Duc Vu","family":"Nguyen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Van","family":"Van Chau","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sinh","family":"Van Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,20]]},"reference":[{"key":"38_CR1","unstructured":"Yi, D., Lei, Z., Liao, S., Li, S.Z.: Learning face representation from scratch (2014). https:\/\/arxiv.org\/abs\/1411.7923"},{"key":"38_CR2","unstructured":"Huang, G.B., Mattar, M., Berg, T., Learned-Miller, E.: Labeled faces in the wild: a database for studying face recognition in unconstrained environments. In: Workshop on Faces in Real Life Images: Detection, Alignment, and Recognition (2008)"},{"key":"38_CR3","doi-asserted-by":"crossref","unstructured":"Nguyen, S.V., Tran, H.M., Maleszka, M.: Geometric modeling: background for processing the 3D objects. Appl. Intell. 51(8), 6182\u20136201 (2021). ISSN: 1573\u20137497","DOI":"10.1007\/s10489-020-02022-6"},{"issue":"3","key":"38_CR4","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1080\/24751839.2021.2008133","volume":"6","author":"S Van Nguyen","year":"2021","unstructured":"Van Nguyen, S., Le, S.T., Tran, M.K., Tran, H.M.: Reconstruction of 3D digital heritage objects for VR and AR applications. J. Inf. Telecommun. 6(3), 254\u2013269 (2021). https:\/\/doi.org\/10.1080\/24751839.2021.2008133. ISSN: 2475\u20131839","journal-title":"J. Inf. Telecommun."},{"key":"38_CR5","doi-asserted-by":"crossref","unstructured":"Van Nguyen, S., Nguyen, D.A., Pham, L.Q.S.: Digitalization of administrative documents - a digital transformation step in practice. In: 8th NAFOSTED Conference on Information and Computer Science (NICS), pp. 519\u2013524. IEEE (2021). 978-1-6654-1001-4\/21\/\\$31.00","DOI":"10.1109\/NICS54270.2021.9701547"},{"issue":"5","key":"38_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s42979-020-00266-0","volume":"1","author":"S Van Nguyen","year":"2020","unstructured":"Van Nguyen, S., Tran, H.M., Le, T.S.: Application of geometric modeling in visualizing the medical image dataset. SN Comput. Sci. 1(5), 1\u201315 (2020). https:\/\/doi.org\/10.1007\/s42979-020-00266-0","journal-title":"SN Comput. Sci."},{"key":"38_CR7","doi-asserted-by":"publisher","unstructured":"Suganthi, S.T., Ayoobkhan, M.U.A., Venkatachalam, K.V., Bacanin, N., Stepan, H., Pavel, T.: Deep learning model for deep fake face recognition and detection. PeerJ Comput. Sci. 8, e881 (2022). https:\/\/doi.org\/10.7717\/peerj-cs.881","DOI":"10.7717\/peerj-cs.881"},{"key":"38_CR8","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1755\/1\/012006","volume":"1755","author":"KH Teoh","year":"2021","unstructured":"Teoh, K.H., Ismail, R.C., Naziri, S.Z.M., Hussin, R., Isa, M.N.M., Basir, M.S.S.M.: Face recognition and identification using deep learning approach. J. Phys. Conf. Ser. 1755, 012006 (2021)","journal-title":"J. Phys. Conf. Ser."},{"issue":"6","key":"38_CR9","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional. J. Commun. ACM 60(6), 84\u201390 (2017). https:\/\/doi.org\/10.1145\/3065386","journal-title":"J. Commun. ACM"},{"key":"38_CR10","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: International Conference on Learning Representations (2015). http:\/\/arxiv.org\/abs\/1409.1556"},{"key":"38_CR11","doi-asserted-by":"crossref","unstructured":"Szegedy, C., et al.: Going deeper with convolutions (2014). https:\/\/doi.org\/10.48550\/arXiv.1409.4842","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"38_CR12","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"38_CR13","doi-asserted-by":"publisher","unstructured":"Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2818\u20132826 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.308","DOI":"10.1109\/CVPR.2016.308"},{"key":"38_CR14","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Ioffe, S., Vanhouke, V., Alemi, A.A.: Inception-v4, inception-ResNet and the impact of residual connections on learning. In: AAAI 2017 Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, pp. 4278\u20134284 (2017)","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"38_CR15","doi-asserted-by":"publisher","unstructured":"Schroff, F., Kalenichenko, D., Philbin, J.: FaceNet: a unified embedding for face recognition and clustering. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2015, pp. 815\u2013823 (2015). https:\/\/doi.org\/10.1109\/CVPR.2015.7298682","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"38_CR16","doi-asserted-by":"publisher","unstructured":"Moungsouy, W., Tawanbunjerd, T., Liamsomboon, N., Kusakunniran, W.: Face recognition under mask-wearing based on residual inception networks. Appl. Comput. Inf. (2022). https:\/\/doi.org\/10.1108\/ACI-09-2021-0256","DOI":"10.1108\/ACI-09-2021-0256"},{"key":"38_CR17","doi-asserted-by":"publisher","unstructured":"Masood, S., Ahsan, U., Munawwar, F., Rizvi, D.R., Ahmed, M.: Scene recognition from image using convolutional neural network. J. Procedia Comput. Sci. 167, 1005\u20131012. https:\/\/doi.org\/10.1016\/j.procs.2020.03.400. ISSN 1877\u20130509","DOI":"10.1016\/j.procs.2020.03.400"},{"key":"38_CR18","unstructured":"Sun, K., et al.: High-resolution representations for labeling pixels and regions (2019). arXiv:1904.04514v1 [cs.CV]"},{"issue":"2","key":"38_CR19","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1007\/s11766-022-4589-0","volume":"37","author":"S Liang","year":"2022","unstructured":"Liang, S., Zhou, Z., Guo, Y., Gao, X., Zhang, J., Bao, H.: Facial landmark disentangled network with variational autoencoder. J. Appl. Math. 37(2), 290\u2013305 (2022)","journal-title":"J. Appl. Math."},{"key":"38_CR20","unstructured":"AIZOOTECH. Github FaceMaskDetection. Accessed July 2022. https:\/\/github.com\/AIZOOTech\/FaceMaskDetection"},{"key":"38_CR21","unstructured":"Timesler, Facenet-pytorch. https:\/\/github.com\/timesler\/facenet-pytorch"}],"container-title":["Communications in Computer and Information Science","Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-19-8069-5_38","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,9]],"date-time":"2024-10-09T03:46:35Z","timestamp":1728445595000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-19-8069-5_38"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789811980688","9789811980695"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-19-8069-5_38","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"20 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"FDSE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Future Data and Security Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ho Chi Minh City","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vietnam","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 November 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"fdse2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/thefdse.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"170","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"41","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"12","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4 full papers from invited keynote speakers","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}