{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T10:51:47Z","timestamp":1761648707319,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030339036"},{"type":"electronic","value":"9783030339043"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-33904-3_26","type":"book-chapter","created":{"date-parts":[[2019,10,25]],"date-time":"2019-10-25T22:40:05Z","timestamp":1572043205000},"page":"283-293","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Analysis of the Impact of Ear Alignment on Unconstrained Ear Recognition"],"prefix":"10.1007","author":[{"given":"Elaine","family":"Grenot-Castellano","sequence":"first","affiliation":[]},{"given":"Yoanna","family":"Mart\u00ednez-D\u00edaz","sequence":"additional","affiliation":[]},{"given":"Francisco Jos\u00e9","family":"Silva-Mata","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,10,22]]},"reference":[{"key":"26_CR1","doi-asserted-by":"crossref","unstructured":"Abaza, A., Harrison, M.A.F.: Ear recognition: a complete system. In: Biometric and Surveillance Technology for Human and Activity Identification X, vol. 8712, p. 87120N (2013)","DOI":"10.1117\/12.2015946"},{"issue":"3","key":"26_CR2","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1049\/iet-bmt.2017.0208","volume":"7","author":"S Dodge","year":"2018","unstructured":"Dodge, S., Mounsef, J., Karam, L.: Unconstrained ear recognition using deep neural networks. IET Biom. 7(3), 207\u2013214 (2018)","journal-title":"IET Biom."},{"key":"26_CR3","series-title":"Studies in Computational Intelligence","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1007\/978-3-030-03000-1_14","volume-title":"Recent Advances in Computer Vision","author":"\u017d Emer\u0161i\u010d","year":"2019","unstructured":"Emer\u0161i\u010d, \u017d., Kri\u017eaj, J., \u0160truc, V., Peer, P.: Deep ear recognition pipeline. In: Hassaballah, M., Hosny, K.M. (eds.) Recent Advances in Computer Vision. SCI, vol. 804, pp. 333\u2013362. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-03000-1_14"},{"key":"26_CR4","doi-asserted-by":"crossref","unstructured":"Emer\u0161i\u010d, \u017d., et al.: The unconstrained ear recognition challenge. In: IEEE IJCB, pp. 715\u2013724 (2017)","DOI":"10.1109\/BTAS.2017.8272761"},{"key":"26_CR5","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.neucom.2016.08.139","volume":"255","author":"\u017d Emer\u0161i\u010d","year":"2017","unstructured":"Emer\u0161i\u010d, \u017d., \u0160truc, V., Peer, P.: Ear recognition: more than a survey. Neurocomputing 255, 26\u201339 (2017)","journal-title":"Neurocomputing"},{"key":"26_CR6","unstructured":"Emer\u0161i\u010d, \u017d., et al.: The unconstrained ear recognition challenge 2019-arxiv version with appendix. arXiv preprint arXiv:1903.04143 (2019)"},{"issue":"6","key":"26_CR7","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1145\/358669.358692","volume":"24","author":"MA Fischler","year":"1981","unstructured":"Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381\u2013395 (1981)","journal-title":"Commun. ACM"},{"issue":"3","key":"26_CR8","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1049\/iet-bmt.2017.0210","volume":"7","author":"EE Hansley","year":"2018","unstructured":"Hansley, E.E., Segundo, M.P., Sarkar, S.: Employing fusion of learned and handcrafted features for unconstrained ear recognition. IET Biom. 7(3), 215\u2013223 (2018)","journal-title":"IET Biom."},{"key":"26_CR9","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, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"26_CR10","unstructured":"Howard, A.G., et al.: Mobilenets: efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861 (2017)"},{"key":"26_CR11","doi-asserted-by":"crossref","unstructured":"Oravec, M., et al.: Mobile ear recognition application, pp. 1\u20134 (2016)","DOI":"10.1109\/IWSSIP.2016.7502719"},{"key":"26_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1007\/978-3-319-11599-3_16","volume-title":"Secure IT Systems","author":"A Pflug","year":"2014","unstructured":"Pflug, A., Busch, C.: Segmentation and normalization of human ears using cascaded pose regression. In: Bernsmed, K., Fischer-H\u00fcbner, S. (eds.) NordSec 2014. LNCS, vol. 8788, pp. 261\u2013272. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-11599-3_16"},{"key":"26_CR13","unstructured":"Ribi\u010d, M., Emer\u0161i\u010d, \u017d., \u0160truc, V., et al.: Influence of alignment on ear recognition: case study on awe dataset. In: International Electrotechnical and Computer Science Conference (2016)"},{"issue":"5","key":"26_CR14","doi-asserted-by":"publisher","first-page":"49","DOI":"10.14257\/ijsip.2013.6.5.05","volume":"6","author":"W Shu-zhong","year":"2013","unstructured":"Shu-zhong, W.: An improved normalization method for ear feature extraction. IJSIP 6(5), 49\u201356 (2013)","journal-title":"IJSIP"},{"key":"26_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1007\/978-3-642-04070-2_5","volume-title":"Emerging Intelligent Computing Technology and Applications","author":"AP Yazdanpanah","year":"2009","unstructured":"Yazdanpanah, A.P., Faez, K.: Normalizing human ear in proportion to size and rotation. In: Huang, D.-S., Jo, K.-H., Lee, H.-H., Kang, H.-J., Bevilacqua, V. (eds.) ICIC 2009. LNCS, vol. 5754, pp. 37\u201345. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-3-642-04070-2_5"},{"key":"26_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"562","DOI":"10.1007\/978-3-319-97909-0_60","volume-title":"Biometric Recognition","author":"L Yuan","year":"2018","unstructured":"Yuan, L., Zhao, H., Zhang, Y., Wu, Z.: Ear alignment based on convolutional neural network. In: Zhou, J., et al. (eds.) CCBR 2018. LNCS, vol. 10996, pp. 562\u2013571. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-97909-0_60"},{"key":"26_CR17","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Zaferiou, S.: Deformable models of ears in-the-wild for alignment and recognition. In: 12th IEEE International Conference on Automatic Face & Gesture Recognition, pp. 626\u2013633 (2017)","DOI":"10.1109\/FG.2017.79"}],"container-title":["Lecture Notes in Computer Science","Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-33904-3_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T14:07:52Z","timestamp":1710252472000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-33904-3_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030339036","9783030339043"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-33904-3_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"22 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CIARP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Iberoamerican Congress on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Havana","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cuba","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ciarp2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ciarp.uci.cu\/","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":"OCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"128","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":"70","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":"55% - 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":"3","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":"This content has been made available to all.","name":"free","label":"Free to read"}]}}