{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T22:31:05Z","timestamp":1786487465983,"version":"build-2736575974"},"reference-count":55,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T00:00:00Z","timestamp":1784160000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013129","name":"Korea Ministry of SMEs and Startups","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014188","name":"Korea Ministry of Science and ICT","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.patcog.2026.114469","type":"journal-article","created":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T15:01:21Z","timestamp":1784214081000},"page":"114469","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PE","title":["Facial age estimation using age-region joint distribution"],"prefix":"10.1016","volume":"180","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7137-7986","authenticated-orcid":false,"given":"Dongjun","family":"Choi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sangwook","family":"Yoo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.patcog.2026.114469_b1","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1038\/cr.2015.36","article-title":"Three-dimensional human facial morphologies as robust aging markers","volume":"25","author":"Chen","year":"2015","journal-title":"Cell Res."},{"key":"10.1016\/j.patcog.2026.114469_b2","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1186\/s13148-023-01590-x","article-title":"Epigenetics insights from perceived facial aging","volume":"15","author":"Vladimir","year":"2023","journal-title":"Clin. Epigenetics"},{"key":"10.1016\/j.patcog.2026.114469_b3","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.2147\/CCID.S457080","article-title":"Facial skin aging characteristics of the old-perceived age in a 20\u201340 years old Chinese female population","volume":"17","author":"Quan","year":"2024","journal-title":"Clin. Cosmet. Investig. Dermatol."},{"key":"10.1016\/j.patcog.2026.114469_b4","doi-asserted-by":"crossref","first-page":"510","DOI":"10.1111\/ics.13045","article-title":"Effects of under-eye skin and crow\u2019s feet on perceived facial appearance in women of five ethnic groups","volume":"47","author":"Fink","year":"2025","journal-title":"Int. J. Cosmet. Sci."},{"key":"10.1016\/j.patcog.2026.114469_b5","doi-asserted-by":"crossref","first-page":"890","DOI":"10.1111\/j.1365-2133.2006.07465.x","article-title":"Sebum output as a factor contributing to the size of facial pores","volume":"155","author":"Roh","year":"2006","journal-title":"Br. J. Dermatol."},{"key":"10.1016\/j.patcog.2026.114469_b6","doi-asserted-by":"crossref","unstructured":"D. Yi, Z. Lei, S. Li, Age Estimation by Multi-scale Convolutional Network, in: Asian Conference on Computer Vision, ACCV, 2014, pp. 144\u2013158.","DOI":"10.1007\/978-3-319-16811-1_10"},{"key":"10.1016\/j.patcog.2026.114469_b7","doi-asserted-by":"crossref","unstructured":"M. de Assis Angeloni, R. de Freitas Pereira, H. Pedrini, Age Estimation From Facial Parts Using Compact Multi-Stream Convolutional Neural Networks, in: IEEE\/CVF International Conference on Computer Vision Workshop, ICCVW, 2019, pp. 3039\u20133045.","DOI":"10.1109\/ICCVW.2019.00366"},{"key":"10.1016\/j.patcog.2026.114469_b8","doi-asserted-by":"crossref","first-page":"3249","DOI":"10.18632\/aging.101629","article-title":"PhotoAgeClock: deep learning algorithms for development of non-invasive visual biomarkers of aging","volume":"10","author":"Bobrov","year":"2018","journal-title":"Aging (Albany NY)"},{"key":"10.1016\/j.patcog.2026.114469_b9","doi-asserted-by":"crossref","unstructured":"B.-B. Gao, H.-Y. Zhou, J. Wu, X. Geng, Age Estimation Using Expectation of Label Distribution Learning, in: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018, pp. 712\u2013718.","DOI":"10.24963\/ijcai.2018\/99"},{"key":"10.1016\/j.patcog.2026.114469_b10","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2019.107178","article-title":"Deep label refinement for age estimation","volume":"100","author":"Li","year":"2020","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114469_b11","doi-asserted-by":"crossref","first-page":"4767","DOI":"10.1109\/TIP.2022.3155944","article-title":"FP-age: Leveraging face parsing attention for facial age estimation in the wild","volume":"34","author":"Lin","year":"2021","journal-title":"IEEE Trans. Image Process.: A Publ. IEEE Signal Process. Soc."},{"key":"10.1016\/j.patcog.2026.114469_b12","doi-asserted-by":"crossref","unstructured":"Z. Liu, Y. Lin, Y. Cao, H. Hu, Y. Wei, Z. Zhang, S. Lin, B. Guo, Swin Transformer: Hierarchical Vision Transformer using Shifted Windows, in: 2021 IEEE\/CVF International Conference on Computer Vision, ICCV, 2021, pp. 10012\u201310022.","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"10.1016\/j.patcog.2026.114469_b13","doi-asserted-by":"crossref","first-page":"145","DOI":"10.3390\/data8100145","article-title":"Attention-based human age estimation from face images to enhance public security","volume":"8","author":"Rahman","year":"2023","journal-title":"Data"},{"key":"10.1016\/j.patcog.2026.114469_b14","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.patrec.2025.01.005","article-title":"Enhancing facial age estimation with local and global multi-attention mechanisms","volume":"189","author":"Liu","year":"2025","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.patcog.2026.114469_b15","doi-asserted-by":"crossref","unstructured":"K. He, X. Zhang, S. Ren, J. Sun, Deep Residual Learning for Image Recognition, in: IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2016, pp. 770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"10.1016\/j.patcog.2026.114469_b16","unstructured":"M. Tan, Q.V. Le, EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks, in: International Conference on Machine Learning, ICML, 2019, pp. 6105\u20136114."},{"key":"10.1016\/j.patcog.2026.114469_b17","doi-asserted-by":"crossref","unstructured":"Z. Liu, H. Mao, C. Wu, C. Feichtenhofer, T. Darrell, S. Xie, A ConvNet for the 2020s, in: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2022, pp. 11976\u201311986.","DOI":"10.1109\/CVPR52688.2022.01167"},{"key":"10.1016\/j.patcog.2026.114469_b18","doi-asserted-by":"crossref","unstructured":"H. Pan, H. Han, S. Shan, X. Chen, Mean-Variance Loss for Deep Age Estimation from a Face, in: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2018, pp. 5285\u20135294.","DOI":"10.1109\/CVPR.2018.00554"},{"key":"10.1016\/j.patcog.2026.114469_b19","doi-asserted-by":"crossref","unstructured":"Z. Zhao, P. Qian, Y. Hou, Z. Zeng, Adaptive Mean-Residue Loss for Robust Facial Age Estimation, in: IEEE International Conference on Multimedia and Expo, ICME, 2022, pp. 1\u20136.","DOI":"10.1109\/ICME52920.2022.9859703"},{"key":"10.1016\/j.patcog.2026.114469_b20","doi-asserted-by":"crossref","unstructured":"Q. Li, J. Wang, Z. Yao, Y. Li, P. Yang, J. Yan, C. Wang, S. Pu, Unimodal-Concentrated Loss: Fully Adaptive Label Distribution Learning for Ordinal Regression, in: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2022, pp. 20481\u201320490.","DOI":"10.1109\/CVPR52688.2022.01986"},{"key":"10.1016\/j.patcog.2026.114469_b21","doi-asserted-by":"crossref","unstructured":"R. Rothe, R. Timofte, L.V. Gool, DEX: Deep EXpectation of Apparent Age from a Single Image, in: IEEE International Conference on Computer Vision Workshop, ICCVW, 2015, pp. 252\u2013257.","DOI":"10.1109\/ICCVW.2015.41"},{"key":"10.1016\/j.patcog.2026.114469_b22","doi-asserted-by":"crossref","unstructured":"Z. Niu, M. Zhou, L. Wang, X. Gao, G. Hua, Ordinal Regression with Multiple Output CNN for Age Estimation, in: IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2016, pp. 4920\u20134928.","DOI":"10.1109\/CVPR.2016.532"},{"key":"10.1016\/j.patcog.2026.114469_b23","doi-asserted-by":"crossref","unstructured":"S. Chen, C. Zhang, M. Dong, J. Le, M. Rao, Using Ranking-CNN for Age Estimation, in: IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2017, pp. 742\u2013751.","DOI":"10.1109\/CVPR.2017.86"},{"key":"10.1016\/j.patcog.2026.114469_b24","doi-asserted-by":"crossref","first-page":"2401","DOI":"10.1109\/TPAMI.2013.51","article-title":"Facial age estimation by learning from label distributions","volume":"35","author":"Geng","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.patcog.2026.114469_b25","doi-asserted-by":"crossref","first-page":"2825","DOI":"10.1109\/TIP.2017.2689998","article-title":"Deep label distribution learning with label ambiguity","volume":"26","author":"Gao","year":"2016","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.patcog.2026.114469_b26","doi-asserted-by":"crossref","unstructured":"X. Wen, B. Li, H. Guo, Z. Liu, G. Hu, M. Tang, J. Wang, Adaptive Variance Based Label Distribution Learning for Facial Age Estimation, in: European Conference on Computer Vision, ECCV, 2020, pp. 379\u2013395.","DOI":"10.1007\/978-3-030-58592-1_23"},{"key":"10.1016\/j.patcog.2026.114469_b27","series-title":"Neural Information Processing Systems","first-page":"3988","article-title":"Learning to learn by gradient descent by gradient descent","author":"Andrychowicz","year":"2016"},{"key":"10.1016\/j.patcog.2026.114469_b28","doi-asserted-by":"crossref","unstructured":"S. Suzuki, S. Yamaguchi, S. Takeda, T. Kaneko, S. Orihashi, R. Masumura, Distribution Highlighted Reference-based Label Distribution Learning for Facial Age Estimation, in: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, WACV, 2026, pp. 6464\u20136473.","DOI":"10.1109\/WACV61042.2026.00625"},{"key":"10.1016\/j.patcog.2026.114469_b29","doi-asserted-by":"crossref","unstructured":"P. Chen, X. Zhang, Y. Li, J. Tao, B. Xiao, B. Wang, Z. Jiang, DAA: A Delta Age AdaIN operation for age estimation via binary code transformer, in: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2023, pp. 15836\u201315845.","DOI":"10.1109\/CVPR52729.2023.01520"},{"key":"10.1016\/j.patcog.2026.114469_b30","doi-asserted-by":"crossref","unstructured":"X. Huang, S.J. Belongie, Arbitrary Style Transfer in Real-Time with Adaptive Instance Normalization, in: IEEE International Conference on Computer Vision, ICCV, 2017, pp. 1501\u20131510.","DOI":"10.1109\/ICCV.2017.167"},{"key":"10.1016\/j.patcog.2026.114469_b31","doi-asserted-by":"crossref","unstructured":"G. Guo, G. Mu, Y. Fu, T.S. Huang, Human age estimation using bio-inspired features, in: IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2009, pp. 112\u2013119.","DOI":"10.1109\/CVPR.2009.5206681"},{"key":"10.1016\/j.patcog.2026.114469_b32","doi-asserted-by":"crossref","unstructured":"M.Y. Eldib, M.A. El-Saban, Human age estimation using enhanced bio-inspired features (EBIF), in: IEEE International Conference on Image Processing, ICIP, 2010, pp. 1589\u20131592.","DOI":"10.1109\/ICIP.2010.5651440"},{"key":"10.1016\/j.patcog.2026.114469_b33","doi-asserted-by":"crossref","first-page":"1754","DOI":"10.1016\/j.procs.2015.02.126","article-title":"Age estimation from face image using wrinkle features","volume":"46","author":"Jana","year":"2015","journal-title":"Procedia Comput. Sci."},{"key":"10.1016\/j.patcog.2026.114469_b34","unstructured":"C.-C. Ng, M.H. Yap, N. Costen, B. Li, An investigation on local wrinkle-based extractor of age estimation, in: International Conference on Computer Vision Theory and Applications, VISAPP, Vol. 1, 2014, pp. 675\u2013681."},{"key":"10.1016\/j.patcog.2026.114469_b35","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.imavis.2017.08.005","article-title":"Hybrid ageing patterns for face age estimation","volume":"69","author":"Ng","year":"2017","journal-title":"Image Vis. Comput."},{"key":"10.1016\/j.patcog.2026.114469_b36","doi-asserted-by":"crossref","first-page":"97","DOI":"10.12659\/MSM.889946","article-title":"Age estimation using level of eyebrow and eyelash whitening","volume":"20","author":"Kantarc\u0131","year":"2014","journal-title":"Med. Sci. Monit. : Int. Med. J. Exp. Clin. Res."},{"key":"10.1016\/j.patcog.2026.114469_b37","doi-asserted-by":"crossref","unstructured":"B. Zhou, A. Khosla, \u00c0. Lapedriza, A. Oliva, A. Torralba, Learning Deep Features for Discriminative Localization, in: IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2015, pp. 2921\u20132929.","DOI":"10.1109\/CVPR.2016.319"},{"key":"10.1016\/j.patcog.2026.114469_b38","doi-asserted-by":"crossref","DOI":"10.3389\/fnins.2023.1136934","article-title":"Face-based age estimation using improved swin transformer with attention-based convolution","volume":"17","author":"Shi","year":"2023","journal-title":"Front. Neurosci."},{"key":"10.1016\/j.patcog.2026.114469_b39","doi-asserted-by":"crossref","unstructured":"J. Hu, L. Shen, S. Albanie, G. Sun, E. Wu, Squeeze-and-Excitation Networks, in: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2018, pp. 7132\u20137141.","DOI":"10.1109\/CVPR.2018.00745"},{"key":"10.1016\/j.patcog.2026.114469_b40","unstructured":"C.-F. Chen, R. Panda, Q. Fan, RegionViT: Regional-to-Local Attention for Vision Transformers, in: The Tenth International Conference on Learning Representations, ICLR, 2022."},{"key":"10.1016\/j.patcog.2026.114469_b41","unstructured":"C. Lee, J. Heo, C.-S. Kim, GATE: Gaussian-Attentive Transformer for Uncertainty-Aware Age Estimation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings, 2026, pp. 8736\u20138745."},{"key":"10.1016\/j.patcog.2026.114469_b42","unstructured":"I. Sergey, S. Christian, Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift, in: International Conference on Machine Learning, ICML, 2015, pp. 448\u2013456."},{"key":"10.1016\/j.patcog.2026.114469_b43","doi-asserted-by":"crossref","unstructured":"R. Girshick, Fast R-CNN, in: Proceedings of the IEEE International Conference on Computer Vision, 2015, pp. 1440\u20131448.","DOI":"10.1109\/ICCV.2015.169"},{"key":"10.1016\/j.patcog.2026.114469_b44","unstructured":"lululab Inc., LUMINI KIOSK V2 and LUMINI SDK, https:\/\/lulu-lab.com\/page_en\/b2b.php."},{"key":"10.1016\/j.patcog.2026.114469_b45","doi-asserted-by":"crossref","unstructured":"Z. Zhang, Y. Song, H. Qi, Age Progression\/Regression by Conditional Adversarial Autoencoder, in: IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2017, pp. 4352\u20134360.","DOI":"10.1109\/CVPR.2017.463"},{"key":"10.1016\/j.patcog.2026.114469_b46","doi-asserted-by":"crossref","unstructured":"J. Paplh\u00e1m, V. Franc, A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark, in: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2024, pp. 1196\u20131205.","DOI":"10.1109\/CVPR52733.2024.00120"},{"key":"10.1016\/j.patcog.2026.114469_b47","doi-asserted-by":"crossref","unstructured":"Y. Zhang, L. Liu, C. Li, C.C. Loy, Quantifying Facial Age by Posterior of Age Comparisons, in: British Machine Vision Conference, BMVC, 2017, pp. 108.1\u2013108.12.","DOI":"10.5244\/C.31.108"},{"key":"10.1016\/j.patcog.2026.114469_b48","doi-asserted-by":"crossref","unstructured":"T.-Y. Yang, Y.-H. Huang, Y.-Y. Lin, P.-C. Hsiu, Y.-Y. Chuang, SSR-Net: A Compact Soft Stagewise Regression Network for Age Estimation, in: International Joint Conference on Artificial Intelligence, IJCAI, 2018, pp. 1078\u20131084.","DOI":"10.24963\/ijcai.2018\/150"},{"key":"10.1016\/j.patcog.2026.114469_b49","series-title":"YOLOv5","author":"Jocher","year":"2020"},{"key":"10.1016\/j.patcog.2026.114469_b50","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"248","article-title":"ImageNet: A large-scale hierarchical image database","author":"Deng","year":"2009"},{"key":"10.1016\/j.patcog.2026.114469_b51","unstructured":"D.P. Kingma, J. Ba, Adam: A Method for Stochastic Optimization, in: International Conference on Learning Representation, ICLR, 2015."},{"key":"10.1016\/j.patcog.2026.114469_b52","unstructured":"I. Loshchilov, F. Hutter, SGDR: Stochastic Gradient Descent with Warm Restarts, in: International Conference on Learning Representation, ICLR, 2017."},{"key":"10.1016\/j.patcog.2026.114469_b53","unstructured":"A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, J. Uszkoreit, N. Houlsby, An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale, in: 9th International Conference on Learning Representations, ICLR, 2021."},{"key":"10.1016\/j.patcog.2026.114469_b54","doi-asserted-by":"crossref","first-page":"3108","DOI":"10.1109\/TNNLS.2020.3009523","article-title":"Distilling ordinal relation and dark knowledge for facial age estimation","volume":"32","author":"Zhao","year":"2020","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.patcog.2026.114469_b55","series-title":"International Journal of Computer Vision","first-page":"618","article-title":"Grad-CAM: Visual explanations from deep networks via gradient-based localization","author":"Selvaraju","year":"2017"}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326014330?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326014330?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T22:09:29Z","timestamp":1786486169000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320326014330"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":55,"alternative-id":["S0031320326014330"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2026.114469","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Facial age estimation using age-region joint distribution","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2026.114469","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"114469"}}