{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T18:43:32Z","timestamp":1761677012290,"version":"3.40.5"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T00:00:00Z","timestamp":1634688000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T00:00:00Z","timestamp":1634688000000},"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":["Int. J. Autom. Comput."],"published-print":{"date-parts":[[2021,12]]},"DOI":"10.1007\/s11633-021-1309-9","type":"journal-article","created":{"date-parts":[[2021,10,19]],"date-time":"2021-10-19T19:39:26Z","timestamp":1634672366000},"page":"915-925","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Improved Network for Face Recognition Based on Feature Super Resolution Method"],"prefix":"10.1007","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2984-7849","authenticated-orcid":false,"given":"Ling-Yi","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0187-6181","authenticated-orcid":false,"given":"Zoran","family":"Gajic","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,20]]},"reference":[{"issue":"4","key":"1309_CR1","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1007\/s11633-014-0872-8","volume":"12","author":"Y Y Zheng","year":"2015","unstructured":"Y. Y. Zheng, J. Yao. Multi-angle face detection based on DP-Adaboost. International Journal of Automation and Computing, vol. 12, no. 4, pp. 421\u2013431, 2015. DOI: https:\/\/doi.org\/10.1007\/s11633-014-0872-8.","journal-title":"International Journal of Automation and Computing"},{"issue":"5","key":"1309_CR2","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1007\/s11633-014-0835-0","volume":"11","author":"L Wang","year":"2014","unstructured":"L. Wang, R. F. Li, K. Wang, J. Chen. Feature representation for facial expression recognition based on FACS and LBP. International Journal of Automation and Computing, vol. 11, no. 5, pp. 459\u2013468, 2014. DOI: https:\/\/doi.org\/10.1007\/s11633-014-0835-0.","journal-title":"International Journal of Automation and Computing"},{"issue":"6","key":"1309_CR3","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1007\/s11633-015-0901-2","volume":"12","author":"H S Du","year":"2015","unstructured":"H. S. Du, Q. P. Hu, D. F. Qiao, I. Pitas. Robust face recog-nition via low-rank sparse representation-based classification. International Journal of Automation and Computing, vol. 12, no. 6, pp. 579\u2013587, 2015. DOI: https:\/\/doi.org\/10.1007\/s11633-015-0901-2.","journal-title":"International Journal of Automation and Computing"},{"key":"1309_CR4","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1109\/SIB-GRAPI.2018.00067","volume-title":"Proceedings of the 31st SIBGRAPI Conference on Graphics, Patterns and Images, IEEE, Parana, Brazil","author":"I Masi","year":"2018","unstructured":"I. Masi, Y. Wu, T. Hassner, P. Natarajan. Deep face recognition: A survey. In Proceedings of the 31st SIBGRAPI Conference on Graphics, Patterns and Images, IEEE, Parana, Brazil, pp. 471\u2013478, 2018. DOI:: https:\/\/doi.org\/10.1109\/SIB-GRAPI.2018.00067."},{"key":"1309_CR5","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1109\/ICOT.2016.8278983","volume-title":"Proceedings of International Conference on Orange Technologies, IEEE, Melbourne, Australia","author":"B Prihasto","year":"2016","unstructured":"B. Prihasto, S. Choirunnisa, M. I. Nurdiansyah, S. Mathulaprangsan, V. C. M. Chu, S. H. Chen, J. C. Wang. A survey of deep face recognition in the wild. In Proceedings of International Conference on Orange Technologies, IEEE, Melbourne, Australia, pp. 76\u201379, 2016. DOI:: https:\/\/doi.org\/10.1109\/ICOT.2016.8278983."},{"issue":"4","key":"1309_CR6","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1145\/954339.954342","volume":"35","author":"W Zhao","year":"2003","unstructured":"W. Zhao, R. Chellappa, P. J. Phillips, A. Rosenfeld. Face recognition: A literature survey. ACM Computing Surveys, vol. 35, no. 4, pp. 399\u2013458, 2003. DOI:: https:\/\/doi.org\/10.1145\/954339.954342.","journal-title":"ACM Computing Surveys"},{"issue":"11","key":"1309_CR7","doi-asserted-by":"publisher","first-page":"2876","DOI":"10.1016\/j.patcog.2009.04.017","volume":"42","author":"X Z Zhang","year":"2009","unstructured":"X. Z. Zhang, Y. S. Gao. Face recognition across pose: A review. Pattern Recognition, vol. 42, no. 11, pp. 2876\u20132896, 2009. DOI:: https:\/\/doi.org\/10.1016\/j.patcog.2009.04.017.","journal-title":"Pattern Recognition"},{"issue":"16","key":"1309_CR8","doi-asserted-by":"publisher","first-page":"9510","DOI":"10.1109\/JSEN.2020.2986839","volume":"20","author":"C H Lin","year":"2020","unstructured":"C. H. Lin, Z. H. Wang, G. J. Jong. A de-identification face recognition using extracted thermal features based on deep learning. IEEE Sensors Journal, vol. 20, no. 16, pp. 9510\u20139517, 2020. DOI::https:\/\/doi.org\/10.1109\/JSEN.2020.2986098.","journal-title":"IEEE Sensors Journal"},{"issue":"10","key":"1309_CR9","doi-asserted-by":"publisher","first-page":"11382","DOI":"10.1109\/JSEN.2020.2997182","volume":"21","author":"W Yang","year":"2021","unstructured":"W. Yang, H. W. Gao, Y. Q. Jiang, J. H. Yu, J. Sun, J. G. Liu, Z. J. Ju. A cascaded feature pyramid network with non-backward propagation for facial expression recogntion. IEEE Sensors Journal, vol. 21, no. 10, pp. 11382\u201311392, 2021. DOI: https:\/\/doi.org\/10.1109\/JSEN.2020.2997182.","journal-title":"IEEE Sensors Journal"},{"key":"1309_CR10","doi-asserted-by":"publisher","first-page":"1701","DOI":"10.1109\/CVPR.2014.220","volume-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, IEEE, Columbus, USA","author":"Y Taigman","year":"2014","unstructured":"Y. Taigman, M. Yang, M. A. Ranzato, L. Wolf. DeepFace: Closing the gap to human-level performance in face verification. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, IEEE, Columbus, USA, pp. 1701\u20131708, 2014. DOI: https:\/\/doi.org\/10.1109\/CVPR.2014.220."},{"key":"1309_CR11","doi-asserted-by":"publisher","first-page":"815","DOI":"10.1109\/CVPR.2015.7298682","volume-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","author":"F Schroff","year":"2015","unstructured":"F. Schroff, D. Kalenichenko, J. Philbin. FaceNet: A unified embedding for face recognition and clustering. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, IEEE, Boston, USA, pp. 815\u2013823, 2015. DOI: https:\/\/doi.org\/10.1109\/CVPR.2015.7298682."},{"key":"1309_CR12","doi-asserted-by":"publisher","DOI":"10.5244\/C.29.41","volume-title":"Proceedings of the British Machine Vision Conference, Swansea, UK","author":"O M Parkhi","year":"2015","unstructured":"O. M. Parkhi, A. Vedaldi, A. Zisserman. Deep face recognition. In Proceedings of the British Machine Vision Conference, Swansea, UK, 2015. DOI: https:\/\/doi.org\/10.5244\/C.29.41."},{"key":"1309_CR13","doi-asserted-by":"publisher","first-page":"4685","DOI":"10.1109\/CVPR.2019.00482","volume-title":"Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"J K Deng","year":"2019","unstructured":"J. K. Deng, J. Guo, N. N. Xue, S. Zafeiriou. ArcFace: Additive angular margin loss for deep face recognition. In Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition, IEEE, Long Beach, USA, pp. 4685\u20134694, 2019. DOI: https:\/\/doi.org\/10.1109\/CVPR.2019.00482."},{"key":"1309_CR14","volume-title":"Technical Report, Technical Report 07-49","author":"G B Huang","year":"2007","unstructured":"G. B. Huang, M. Ramesh, T. Berg, E. Learned-Miller. Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments, Technical Report, Technical Report 07-49, University of Massachusetts, Amherst, USA, 2007."},{"key":"1309_CR15","doi-asserted-by":"publisher","first-page":"770","DOI":"10.1109\/CVPR.2016.90","volume-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","author":"K M He","year":"2016","unstructured":"K. M. He, X. Y. Zhang, S. Q. Ren, J. Sun. Deep residual learning for image recognition. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, IEEE, Las Vegas, USA, pp. 770\u2013778, 2016. DOI: https:\/\/doi.org\/10.1109\/CVPR.2016.90."},{"key":"1309_CR16","doi-asserted-by":"publisher","first-page":"2746","DOI":"10.1109\/CVPR.2015.7298891","volume-title":"In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","author":"Y Taigman","year":"2015","unstructured":"Y. Taigman, M. Yang, M. A. Ranzato, L. Wolf. Web-scale training for face identification. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, IEEE, Boston, USA, pp. 2746\u20132754, 2015. DOI: https:\/\/doi.org\/10.1109\/CVPR.2015.7298891."},{"key":"1309_CR17","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2018.00020","volume-title":"Proceedings of the 13th IEEE International Conference on Automatic Face & Gesture Recognition","author":"Q Cao","year":"2018","unstructured":"Q. Cao, L. Shen, W. D. Xie, O. M. Parkhi, A. Zisserman. VGGFace2: A dataset for recognising faces across pose and age. In Proceedings of the 13th IEEE International Conference on Automatic Face & Gesture Recognition, IEEE, Xi\u2019an, China, 2018. DOI: https:\/\/doi.org\/10.1109\/FG.2018.00020."},{"key":"1309_CR18","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1007\/978-3-319-46487-9_6","volume-title":"Proceedings of the 14th European Conference on Computer Vision","author":"Y D Guo","year":"2016","unstructured":"Y. D. Guo, L. Zhang, Y. X. Hu, X. D. He, J. F. Gao. MS-Celeb-1M: A dataset and benchmark for large-scale face recognition. In Proceedings of the 14th European Conference on Computer Vision, Springer, Amsterdam, Netherlands, pp. 87\u2013102, 2016. DOI: https:\/\/doi.org\/10.1007\/978-3-319-46487-9_6."},{"key":"1309_CR19","volume-title":"Learning face representation from scratch","author":"D Yi","year":"2014","unstructured":"D. Yi, Z. Lei, S. C. Liao, S. Z. Li. Learning face representation from scratch. [Online], Available: https:\/\/arxiv.org\/abs\/1411.7923, 2014."},{"key":"1309_CR20","doi-asserted-by":"publisher","DOI":"10.1109\/BTAS.2009.5339025","volume-title":"Proceedings of the 3rd International Conference on Biometrics: Theory, Applications, and Systems","author":"Y M Lui","year":"2009","unstructured":"Y. M. Lui, D. Bolme, B. A. Draper, J. R. Beveridge, G. Givens, P. J. Phillips. A meta-analysis of face recognition covariates. In Proceedings of the 3rd International Conference on Biometrics: Theory, Applications, and Systems, IEEE, Washington, USA, 2009. DOI: https:\/\/doi.org\/10.1109\/BTAS.2009.5339025."},{"issue":"1","key":"1309_CR21","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1109\/TIP.2011.2162423","volume":"21","author":"W W Zou","year":"2012","unstructured":"W. W. Zou, P. C. Yuen. Very low resolution face recognition problem. IEEE Transactions on Image Processing, vol. 21, no. 1, pp. 327\u2013340, 2012. DOI: https:\/\/doi.org\/10.1109\/TIP.2011.2162423.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"10","key":"1309_CR22","doi-asserted-by":"publisher","first-page":"1039","DOI":"10.1016\/j.imavis.2006.02.026","volume":"24","author":"J D van Ouwerkerk","year":"2006","unstructured":"J. D. van Ouwerkerk. Image super-resolution survey. Image and Vision Computing, vol. 24, no. 10, pp. 1039\u20131052, 2006. DOI: https:\/\/doi.org\/10.1016\/j.imavis.2006.02.026.","journal-title":"Image and Vision Computing"},{"key":"1309_CR23","volume-title":"Deep joint face hallucination and recognition","author":"J Y Wu","year":"2016","unstructured":"J. Y. Wu, S. Y. Ding, W. Xu, H. Y. Chao. Deep joint face hallucination and recognition. [Online], Available: https:\/\/arxiv.org\/abs\/1611.08091, 2016."},{"issue":"4","key":"1309_CR24","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1109\/LSP.2018.2810121","volume":"25","author":"Z Lu","year":"2018","unstructured":"Z. Lu, X. D. Jiang, A. Kot. Deep coupled ResNet for low-resolution face recognition. IEEE Signal Processing Letters, vol. 25, no. 4, pp. 526\u2013530, 2018. DOI: https:\/\/doi.org\/10.1109\/LSP.2018.2810121..","journal-title":"IEEE Signal Processing Letters"},{"key":"1309_CR25","doi-asserted-by":"publisher","DOI":"10.1109\/ET2ECN.2012.6470098","volume-title":"Proceedings of the 1st International Conference on Emerging Technology Trends in Electronics, Communication & Networking","author":"A J. Shah","year":"2012","unstructured":"A. J. Shah, S. B. Gupta. Image super resolution-A survey. In Proceedings of the 1st International Conference on Emerging Technology Trends in Electronics, Communication & Networking, IEEE, Surat, India, 2012. DOI: https:\/\/doi.org\/10.1109\/ET2ECN.2012.6470098."},{"key":"1309_CR26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-20893-6_38","volume-title":"Low-resolution face recognition","author":"Z Y Cheng","year":"2019","unstructured":"Z. Y. Cheng, X. T. Zhu, S. G. Gong. Low-resolution face recognition. [Online], Available: https:\/\/arxiv.org\/abs\/1811.08965, 2019."},{"issue":"8","key":"1309_CR27","doi-asserted-by":"publisher","first-page":"2000","DOI":"10.1109\/TIFS.2018.2890812","volume":"14","author":"P Li","year":"2019","unstructured":"P. Li, L. Prieto, D. Mery, P. J. Flynn. On low-resolution face recognition in the wild: Comparisons and new techniques. IEEE Transactions on Information Forensics and Security, vol. 14, no. 8, pp. 2000\u20132012, 2019. DOI: https:\/\/doi.org\/10.1109\/TIFS.2018.2890812..","journal-title":"IEEE Transactions on Information Forensics and Security"},{"key":"1309_CR28","doi-asserted-by":"publisher","first-page":"75470","DOI":"10.1109\/ACCESS.2021.3080712","volume":"9","author":"L S Luevano","year":"2021","unstructured":"L. S. Luevano, L. Chang, H. M\u00e9ndez-V\u00e1zquez, Y. Mart\u00ednez-D\u00edaz, M. Gonz\u00e1lez-Mendoza. A study on the performance of unconstrained very low resolution face recognition: Analyzing current trends and new research directions. IEEE Access, vol. 9, pp. 75470\u201375493, 2021. DOI: https:\/\/doi.org\/10.1109\/ACCESS.2021.3080712.","journal-title":"IEEE Access"},{"key":"1309_CR29","doi-asserted-by":"publisher","first-page":"2150","DOI":"10.1109\/TIP.2019.2945835","volume":"29","author":"K Grm","year":"2019","unstructured":"K. Grm, W. J. Scheirer, V. \u0160truc. Face hallucination using cascaded super-resolution and identity priors. IEEE Transactions on Image Processing, vol. 29, pp. 2150\u20132165, 2019. DOI: https:\/\/doi.org\/10.1109\/TIP.2019.2945835.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1309_CR30","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.patcog.2018.01.002","volume":"78","author":"K Nguyen","year":"2018","unstructured":"K. Nguyen, C. Fookes, S. Sridharan, M. Tistarelli, M. Nixon. Super-resolution for biometrics: A comprehensive survey. Pattern Recognition, vol. 78, pp. 23\u201342, 2018. DOI: https:\/\/doi.org\/10.1016\/j.patcog.2018.01.002.","journal-title":"Pattern Recognition"},{"key":"1309_CR31","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1016\/j.patrec.2018.10.034","volume":"116","author":"S Banerjee","year":"2018","unstructured":"S. Banerjee, S. Das. LR-GAN for degraded face recognition. Pattern Recognition Letters, vol. 116, pp. 246\u2013253, 2018. DOI: https:\/\/doi.org\/10.1016\/j.patrec.2018.10.034.","journal-title":"Pattern Recognition Letters"},{"issue":"1","key":"1309_CR32","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1109\/MSP.2017.2765202","volume":"35","author":"A Creswell","year":"2018","unstructured":"A. Creswell, T. White, V. Dumoulin, K. Arulkumaran, B. Sengupta, A. A. Bharath. Generative adversarial networks: An overview. IEEE Signal Processing Magazine, vol. 35, no. 1, pp. 53\u201365, 2018. DOI: https:\/\/doi.org\/10.1109\/MSP.2017.2765202.","journal-title":"IEEE Signal Processing Magazine"},{"issue":"4","key":"1309_CR33","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1007\/s11633-019-1183-x","volume":"16","author":"V K Ha","year":"2019","unstructured":"V. K. Ha, J. C. Ren, X. Y. Xu, S. Zhao, G. Xie, V. Masero, A. Hussain. Deep learning based single image super-resolution: A survey. International Journal of Automation and Computing, vol. 16, no. 4, pp. 413\u2013426, 2019. DOI: https:\/\/doi.org\/10.1007\/s11633-019-1183-x..","journal-title":"International Journal of Automation and Computing"},{"key":"1309_CR34","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1007\/978-3-319-46454-1_37","volume-title":"Proceedings of the 14th European Conference on Computer Vision","author":"S Z. Zhu","year":"2016","unstructured":"S. Z. Zhu, S. F. Liu, C. C. Loy, X. O. Tang. Deep cascaded bi-network for face hallucination. In Proceedings of the 14th European Conference on Computer Vision, Springer, Amsterdam, The Netherlands, pp. 614\u2013630, 2016. DOI: https:\/\/doi.org\/10.1007\/978-3-319-46454-1_37."},{"issue":"11","key":"1309_CR35","doi-asserted-by":"publisher","first-page":"2926","DOI":"10.1109\/TPAMI.2019.2916881","volume":"42","author":"X Yu","year":"2020","unstructured":"X. Yu, B. Fernando, R. Hartley, F. Porikli. Semantic face hallucination: Super-resolving very low-resolution face images with supplementary attributes. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 42, no. 11, pp. 2926\u20132943, 2020. DOI: https:\/\/doi.org\/10.1109\/TPAMI.2019.2916881.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1309_CR36","doi-asserted-by":"publisher","unstructured":"E. Zangeneh, M. Rahmati, Y. Mohsenzadeh. Low resolution face recognition using a two-branch deep convolutional neural network architecture. Expert Systems with Applications, vol. 139, Article number 112854, 2020. DOI: https:\/\/doi.org\/10.1016\/j.eswa.2019.112854.","DOI":"10.1016\/j.eswa.2019.112854"},{"key":"1309_CR37","doi-asserted-by":"publisher","first-page":"3994","DOI":"10.1109\/CVPR.2018.00420","volume-title":"Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"W M Tan","year":"2018","unstructured":"W. M. Tan, B. Yan, B. Bare. Feature super-resolution: Make machine see more clearly. In Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition, IEEE, Salt Lake City, USA, pp. 3994\u20134002, 2018. DOI: https:\/\/doi.org\/10.1109\/CVPR.2018.00420."},{"key":"1309_CR38","doi-asserted-by":"publisher","first-page":"780","DOI":"10.1007\/978-3-030-01240-3_47","volume-title":"Proceedings of the 15th European Conference on Computer Vision","author":"F Wang","year":"2018","unstructured":"F. Wang, L. R. Chen, C. Li, S. Y. Huang, Y. J. Chen, C. Qian, C. C. Loy. The devil of face recognition is in the noise. In Proceedings of the 15th European Conference on Computer Vision, Springer, Munich, Germany, pp. 780\u2013795, 2018. DOI: https:\/\/doi.org\/10.1007\/978-3-030-01240-3_47."}],"container-title":["International Journal of Automation and Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11633-021-1309-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11633-021-1309-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11633-021-1309-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,11,25]],"date-time":"2021-11-25T01:08:26Z","timestamp":1637802506000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11633-021-1309-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,20]]},"references-count":38,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["1309"],"URL":"https:\/\/doi.org\/10.1007\/s11633-021-1309-9","relation":{},"ISSN":["1476-8186","1751-8520"],"issn-type":[{"type":"print","value":"1476-8186"},{"type":"electronic","value":"1751-8520"}],"subject":[],"published":{"date-parts":[[2021,10,20]]},"assertion":[{"value":"17 February 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 July 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 October 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}