{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T22:23:56Z","timestamp":1757629436436,"version":"3.44.0"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032045454","type":"print"},{"value":"9783032045461","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T00:00:00Z","timestamp":1757548800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T00:00:00Z","timestamp":1757548800000},"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":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-04546-1_43","type":"book-chapter","created":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T14:53:40Z","timestamp":1757516020000},"page":"530-541","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["U-FQA: A Unified Face Quality Assessment Score for\u00a0Improved Unknown Identity Detection in\u00a0Facial Recognition Systems"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6059-9014","authenticated-orcid":false,"given":"Agostinho","family":"Freire","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3554-0157","authenticated-orcid":false,"given":"Jo\u00e3o V. R.","family":"de Andrade","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5286-3751","authenticated-orcid":false,"given":"Cristian","family":"Millan-Arias","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6001-3925","authenticated-orcid":false,"given":"Bruno J. T.","family":"Fernandes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0924-5341","authenticated-orcid":false,"given":"Carmelo","family":"Bastos-Filho","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2423-5088","authenticated-orcid":false,"given":"Rodrigo","family":"Monteiro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-0508-233X","authenticated-orcid":false,"given":"Jorge Tortato","family":"Junior","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0708-9487","authenticated-orcid":false,"given":"Alexandre","family":"Krzyzanovski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1248-1064","authenticated-orcid":false,"given":"Luiz Gustavo Schitz Da","family":"Rocha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4348-9291","authenticated-orcid":false,"given":"Alexandre M. A.","family":"Maciel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,11]]},"reference":[{"key":"43_CR1","doi-asserted-by":"publisher","first-page":"35429","DOI":"10.1109\/ACCESS.2023.3266068","volume":"11","author":"M Alansari","year":"2023","unstructured":"Alansari, M., Hay, O.A., Javed, S., Shoufan, A., Zweiri, Y., Werghi, N.: GhostFaceNets: lightweight face recognition model from cheap operations. IEEE Access 11, 35429\u201335446 (2023). https:\/\/doi.org\/10.1109\/ACCESS.2023.3266068","journal-title":"IEEE Access"},{"key":"43_CR2","doi-asserted-by":"crossref","unstructured":"Albiero, V., Ks, K., Vangara, K., Zhang, K., King, M.C., Bowyer, K.W.: Analysis of gender inequality in face recognition accuracy. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision Workshops, pp. 81\u201389 (2020)","DOI":"10.1109\/WACVW50321.2020.9096947"},{"key":"43_CR3","unstructured":"Best-Rowden, L., Jain, A.K.: Automatic face image quality prediction. arXiv preprint arXiv:1706.09887 (2017)"},{"key":"43_CR4","doi-asserted-by":"crossref","unstructured":"Damer, N., Boutros, F., S\u00fc\u00dfmilch, M., Fang, M., Kirchbuchner, F., Kuijper, A.: Masked face recognition: human vs. machine. arXiv preprint arXiv:2103.01924 (2021)","DOI":"10.1049\/bme2.12077"},{"key":"43_CR5","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1007\/s12559-012-9163-2","volume":"5","author":"V Espinosa-Dur\u00f3","year":"2013","unstructured":"Espinosa-Dur\u00f3, V., Faundez-Zanuy, M., Mekyska, J.: A new face database simultaneously acquired in visible, near-infrared and thermal spectrums. Cogn. Comput. 5, 119\u2013135 (2013)","journal-title":"Cogn. Comput."},{"key":"43_CR6","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1007\/s12559-010-9060-5","volume":"2","author":"V Espinosa-Dur\u00f3","year":"2010","unstructured":"Espinosa-Dur\u00f3, V., Faundez-Zanuy, M., Mekyska, J., Monte-Moreno, E.: A criterion for analysis of different sensor combinations with an application to face biometrics. Cogn. Comput. 2, 135\u2013141 (2010)","journal-title":"Cogn. Comput."},{"key":"43_CR7","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"43_CR8","doi-asserted-by":"crossref","unstructured":"Hernandez-Ortega, J., Galbally, J., Fierrez, J., Haraksim, R., Beslay, L.: FaceQNet: quality assessment for face recognition based on deep learning. In: 2019 International Conference on Biometrics (ICB), pp.\u00a01\u20138. IEEE (2019)","DOI":"10.1109\/ICB45273.2019.8987255"},{"key":"43_CR9","unstructured":"Huang, D., Sun, J., Wang, Y.: The BUAA-VISNIR face database instructions. Computer Science Engineering, Beihang University, Beijing, China, Technical Report, IRIP-TR-12-FR-001, vol. 3, no. 3, p. 8 (2012)"},{"key":"43_CR10","doi-asserted-by":"crossref","unstructured":"Meng, Q., Zhao, S., Huang, Z., Zhou, F.: MAGFace: a universal representation for face recognition and quality assessment. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14225\u201314234 (2021)","DOI":"10.1109\/CVPR46437.2021.01400"},{"key":"43_CR11","unstructured":"Merkle, J., Rathgeb, C., Tams, B., Lou, D.P., D\u00f6rsch, A., Drozdowski, P.: State of the art of quality assessment of facial images. arXiv preprint arXiv:2211.08030 (2022)"},{"key":"43_CR12","doi-asserted-by":"crossref","unstructured":"Najafzadeh, N., Kashiani, H., Saadabadi, M.S.E., Talemi, N.A., Malakshan, S.R., Nasrabadi, N.M.: Face image quality vector assessment for biometrics applications. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 511\u2013520 (2023)","DOI":"10.1109\/WACVW58289.2023.00057"},{"key":"43_CR13","doi-asserted-by":"crossref","unstructured":"Ou, F.Z., Li, C., Wang, S., Kwong, S.: CLIB-FIQA: face image quality assessment with confidence calibration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1694\u20131704 (2024)","DOI":"10.1109\/CVPR52733.2024.00167"},{"key":"43_CR14","doi-asserted-by":"crossref","unstructured":"Ou, F.Z., Li, C., Wang, S., Kwong, S.: CLIB-FIQA: face image quality assessment with confidence calibration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1694\u20131704 (2024)","DOI":"10.1109\/CVPR52733.2024.00167"},{"key":"43_CR15","unstructured":"Qi, D., Tan, W., Yao, Q., Liu, J.: YOLO5Face: why reinventing a face detector (2021)"},{"key":"43_CR16","doi-asserted-by":"publisher","first-page":"4057","DOI":"10.1109\/TIP.2019.2956143","volume":"29","author":"K Wang","year":"2020","unstructured":"Wang, K., Peng, X., Yang, J., Meng, D., Qiao, Y.: Region attention networks for pose and occlusion robust facial expression recognition. IEEE Trans. Image Process. 29, 4057\u20134069 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"43_CR17","doi-asserted-by":"crossref","unstructured":"Xu, X., Sarafianos, N., Kakadiaris, I.A.: On improving the generalization of face recognition in the presence of occlusions. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 798\u2013799 (2020)","DOI":"10.1109\/CVPRW50498.2020.00407"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2025"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-04546-1_43","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T14:53:47Z","timestamp":1757516027000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-04546-1_43"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,11]]},"ISBN":["9783032045454","9783032045461"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-04546-1_43","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,11]]},"assertion":[{"value":"11 September 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kaunas","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lithuania","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"34","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/e-nns.org\/icann2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}