{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T10:45:10Z","timestamp":1750675510398,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031485923"},{"type":"electronic","value":"9783031485930"}],"license":[{"start":{"date-parts":[[2023,12,2]],"date-time":"2023-12-02T00:00:00Z","timestamp":1701475200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,2]],"date-time":"2023-12-02T00:00:00Z","timestamp":1701475200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-48593-0_10","type":"book-chapter","created":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T05:03:03Z","timestamp":1701406983000},"page":"133-144","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Deep Facial Phenotyping with\u00a0Mixup Augmentation"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-1783-8665","authenticated-orcid":false,"given":"Jonathan","family":"Campbell","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6719-6584","authenticated-orcid":false,"given":"Mitchell","family":"Dawson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8945-8573","authenticated-orcid":false,"given":"Andrew","family":"Zisserman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3804-2639","authenticated-orcid":false,"given":"Weidi","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2887-2068","authenticated-orcid":false,"given":"Christoffer","family":"Nell\u00e5ker","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,12,2]]},"reference":[{"key":"10_CR1","doi-asserted-by":"crossref","unstructured":"An, X., et al.: Partial FC: training 10 million identities on a single machine. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV) Workshops, pp. 1445\u20131449 (2021)","DOI":"10.1109\/ICCVW54120.2021.00166"},{"key":"10_CR2","doi-asserted-by":"publisher","unstructured":"Cao, Q., Shen, L., Xie, W., Parkhi, O.M., Zisserman, A.: VGGFace2: a dataset for recognising faces across pose and age. In: 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), pp. 67\u201374 (2018). https:\/\/doi.org\/10.1109\/FG.2018.00020","DOI":"10.1109\/FG.2018.00020"},{"key":"10_CR3","unstructured":"Chen, W.Y., Liu, Y.C., Kira, Z., Wang, Y.C., Huang, J.B.: A closer look at few-shot classification. In: International Conference on Learning Representations (2019)"},{"key":"10_CR4","doi-asserted-by":"publisher","unstructured":"Cianci, P., Selicorni, A.: \u201cGestalt diagnosis\u201d for children with suspected genetic syndromes. Ital. J. Pediatr. 41(Suppl 2), A16 (2015). https:\/\/doi.org\/10.1186\/1824-7288-41-S2-A16, https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC4707582\/","DOI":"10.1186\/1824-7288-41-S2-A16"},{"key":"10_CR5","doi-asserted-by":"crossref","unstructured":"Deng, J., Guo, J., Xue, N., Zafeiriou, S.: ArcFace: additive angular margin loss for deep face recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)","DOI":"10.1109\/CVPR.2019.00482"},{"key":"10_CR6","doi-asserted-by":"publisher","unstructured":"van der Donk, R., et al.: Next-generation phenotyping using computer vision algorithms in rare genomic neurodevelopmental disorders. Genet. Med. 21(8), 1719\u20131725 (2019). https:\/\/doi.org\/10.1038\/s41436-018-0404-y, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1098360021016129","DOI":"10.1038\/s41436-018-0404-y"},{"key":"10_CR7","doi-asserted-by":"publisher","unstructured":"Ferry, Q., et al.: Diagnostically relevant facial gestalt information from ordinary photos. eLife 3, e02020 (2014). https:\/\/doi.org\/10.7554\/eLife.02020, publisher: eLife Sciences Publications Ltd","DOI":"10.7554\/eLife.02020"},{"issue":"1","key":"10_CR8","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1038\/s41591-018-0279-0","volume":"25","author":"Y Gurovich","year":"2019","unstructured":"Gurovich, Y., et al.: Identifying facial phenotypes of genetic disorders using deep learning. Nat. Med. 25(1), 60\u201364 (2019)","journal-title":"Nat. Med."},{"key":"10_CR9","doi-asserted-by":"publisher","unstructured":"Hart, T., Hart, P.: Genetic studies of craniofacial anomalies: clinical implications and applications. Orthod. Craniofac. Res. 12(3), 212\u2013220 (2009). https:\/\/doi.org\/10.1111\/j.1601-6343.2009.01455.x","DOI":"10.1111\/j.1601-6343.2009.01455.x"},{"key":"10_CR10","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":"10_CR11","doi-asserted-by":"publisher","unstructured":"Hospedales, T., Antoniou, A., Micaelli, P., Storkey, A.: Meta-learning in neural networks: a survey. IEEE Trans. Pattern Anal. Mach. Intell. 44(9), 5149\u20135169 (2022). https:\/\/doi.org\/10.1109\/TPAMI.2021.3079209, conference Name: IEEE Transactions on Pattern Analysis and Machine Intelligence","DOI":"10.1109\/TPAMI.2021.3079209"},{"key":"10_CR12","doi-asserted-by":"crossref","unstructured":"Hsieh, T.C., et al.: GestaltMatcher facilitates rare disease matching using facial phenotype descriptors. Nature Genet. 54(3), 349\u2013357 (2022). publisher: Nature Publishing Group US New York","DOI":"10.1038\/s41588-021-01010-x"},{"key":"10_CR13","doi-asserted-by":"publisher","unstructured":"Hustinx, A., et al.: Improving deep facial phenotyping for ultra-rare disorder verification using model ensembles. In: 2023 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 5007\u20135017. IEEE, Waikoloa, HI, USA (2023). https:\/\/doi.org\/10.1109\/WACV56688.2023.00499, https:\/\/ieeexplore.ieee.org\/document\/10030218\/","DOI":"10.1109\/WACV56688.2023.00499"},{"key":"10_CR14","doi-asserted-by":"publisher","unstructured":"Jackson, M., Marks, L., May, G.H., Wilson, J.: The genetic basis of disease. Essays Biochem. 62(5), 643\u2013723 (2018). https:\/\/doi.org\/10.1042\/EBC20170053, https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC6279436\/","DOI":"10.1042\/EBC20170053"},{"key":"10_CR15","first-page":"1755","volume":"10","author":"DE King","year":"2009","unstructured":"King, D.E.: Dlib-ml: a machine learning toolkit. J. Mach. Learn. Res. 10, 1755\u20131758 (2009)","journal-title":"J. Mach. Learn. Res."},{"issue":"6","key":"10_CR16","doi-asserted-by":"publisher","first-page":"758","DOI":"10.1002\/mgg3.315","volume":"5","author":"C von der Lippe","year":"2017","unstructured":"von der Lippe, C., Diesen, P.S., Feragen, K.B.: Living with a rare disorder: a systematic review of the qualitative literature. Mol. Genet. Genomic Med. 5(6), 758\u2013773 (2017). https:\/\/doi.org\/10.1002\/mgg3.315","journal-title":"Mol. Genet. Genomic Med."},{"key":"10_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1007\/978-3-030-58555-6_14","volume-title":"Computer Vision \u2013 ECCV 2020","author":"C Luo","year":"2020","unstructured":"Luo, C., Song, C., Zhang, Z.: Generalizing person re-identification by\u00a0camera-aware invariance learning and\u00a0cross-domain mixup. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12360, pp. 224\u2013241. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58555-6_14"},{"volume-title":"Learning to Learn","year":"1998","key":"10_CR18","unstructured":"Thrun, S., Pratt, L. (eds.): Learning to Learn. Kluwer Academic Publishers, USA (1998)"},{"key":"10_CR19","doi-asserted-by":"publisher","unstructured":"Vonikakis, V., Dexter, N.Y.R., Winkler, S.: MorphSet: augmenting categorical emotion datasets with dimensional affect labels using face morphing. In: 2021 IEEE International Conference on Image Processing (ICIP), pp. 2713\u20132717 (2021). https:\/\/doi.org\/10.1109\/ICIP42928.2021.9506566, iSSN: 2381-8549","DOI":"10.1109\/ICIP42928.2021.9506566"},{"key":"10_CR20","doi-asserted-by":"publisher","unstructured":"White, J.D., et al.: Insights into the genetic architecture of the human face. Nat. Genet. 53(1), 45\u201353 (2021). https:\/\/doi.org\/10.1038\/s41588-020-00741-7, http:\/\/www.nature.com\/articles\/s41588-020-00741-7","DOI":"10.1038\/s41588-020-00741-7"},{"key":"10_CR21","unstructured":"Zhang, H., Cisse, M., Dauphin, Y.N., Lopez-Paz, D.: Mixup: beyond empirical risk minimization. In: International Conference on Learning Representations (2018). https:\/\/openreview.net\/forum?id=r1Ddp1-Rb"},{"key":"10_CR22","doi-asserted-by":"crossref","unstructured":"Zhuo, L., Fu, Y., Chen, J., Cao, Y., Jiang, Y.G.: TGDM: target guided dynamic mixup for cross-domain few-shot learning. In: Proceedings of the 30th ACM International Conference on Multimedia, pp. 6368\u20136376 (2022)","DOI":"10.1145\/3503161.3548052"}],"container-title":["Lecture Notes in Computer Science","Medical Image Understanding and Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-48593-0_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T05:10:55Z","timestamp":1701407455000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-48593-0_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,2]]},"ISBN":["9783031485923","9783031485930"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-48593-0_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023,12,2]]},"assertion":[{"value":"2 December 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MIUA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Annual Conference on Medical Image Understanding and Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Aberdeen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 July 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miua2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.abdn.ac.uk\/events\/conferences\/miua2023","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"42","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":"24","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":"0","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":"57% - 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":"2-3","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":"4","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)"}}]}}