{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T15:00:47Z","timestamp":1786978847009,"version":"build-2736575974"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031278174","type":"print"},{"value":"9783031278181","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-27818-1_3","type":"book-chapter","created":{"date-parts":[[2023,3,30]],"date-time":"2023-03-30T06:20:17Z","timestamp":1680157217000},"page":"29-40","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Manga Text Detection with\u00a0Manga-Specific Data Augmentation and\u00a0Its Applications on\u00a0Emotion Analysis"],"prefix":"10.1007","author":[{"given":"Yi-Ting","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei-Ta","family":"Chu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,3,31]]},"reference":[{"issue":"2","key":"3_CR1","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1109\/MMUL.2020.2987895","volume":"27","author":"K Aizawa","year":"2020","unstructured":"Aizawa, K., et al.: Building a manga dataset \u201cManga109\u2019\u2019 with annotations for multimedia applications. IEEE Multimed. 27(2), 8\u201318 (2020)","journal-title":"IEEE Multimed."},{"key":"3_CR2","doi-asserted-by":"crossref","unstructured":"Aramaki, Y., Matsui, Y., Yamasaki, T., Aizawa, K.: Text detection in manga by combining connected-component-based and region-based classifications. In: Proceedings of IEEE ICIP, pp. 2901\u20132905 (2016)","DOI":"10.1109\/ICIP.2016.7532890"},{"key":"3_CR3","unstructured":"Ben-Baruch, E., et al.: Asymmetric loss for multi-label classification. In: Proceedings of ICCV, pp. 82\u201391 (2021)"},{"key":"3_CR4","doi-asserted-by":"crossref","unstructured":"Chu, W.T., Yu, C.C.: Text detection in manga by deep region proposal, classification, and regression. In: Proceedings of IEEE VCIP, pp. 2901\u20132905 (2018)","DOI":"10.1109\/VCIP.2018.8698677"},{"key":"3_CR5","doi-asserted-by":"crossref","unstructured":"Huang, X., Belongie, S.J.: Arbitrary style transfer in real-time with adaptive instance normalization. In: Proceedings of ICCV, pp. 1510\u20131519 (2017)","DOI":"10.1109\/ICCV.2017.167"},{"key":"3_CR6","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial nets. In: Proceedings of CVPR, pp. 1125\u20131134 (2017)","DOI":"10.1109\/CVPR.2017.632"},{"key":"3_CR7","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: Proceedings of International Conference on Neural Information Processing Systems, pp. 1097\u20131105 (2012)"},{"key":"3_CR8","doi-asserted-by":"crossref","unstructured":"Li, W., He, Y., Qi, Y., Li, Z., Tang, Y.: FET-GAN: font and effect transfer via k-shot adaptive instance normalization. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 1717\u20131724 (2020)","DOI":"10.1609\/aaai.v34i02.5535"},{"key":"3_CR9","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. In: Proceedings of Advances in Neural Information Processing Systems (2015)"},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Srivatsan, N., Barron, J.T., Klein, D., Berg-Kirkpatrick, T.: A deep factorization of style and structure in fonts. In: Proceedings of Conference on Empirical Methods in Natural Language Processing (2019)","DOI":"10.18653\/v1\/D19-1225"},{"key":"3_CR11","unstructured":"Tan, M., Le, Q.V.: EfficientNet: rethinking model scaling for convolutional neural networks. In: Proceedings of ICML, pp. 6105\u20136114 (2019)"},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Xie, Y., Chen, X., Sun, L., Lu, Y.: DG-Font: deformable generative networks for unsupervised font generation. In: Proceedings of CVPR, pp. 5130\u20135140 (2021)","DOI":"10.1109\/CVPR46437.2021.00509"},{"issue":"8","key":"3_CR13","doi-asserted-by":"publisher","first-page":"1819","DOI":"10.1109\/TKDE.2013.39","volume":"26","author":"ML Zhang","year":"2014","unstructured":"Zhang, M.L., Zhou, Z.H.: A review on multi-label learning algorithms. IEEE Trans. Knowl. Data Eng. 26(8), 1819\u20131837 (2014)","journal-title":"IEEE Trans. Knowl. Data Eng."}],"container-title":["Lecture Notes in Computer Science","MultiMedia Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-27818-1_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,30]],"date-time":"2023-03-30T06:21:31Z","timestamp":1680157291000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-27818-1_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031278174","9783031278181"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-27818-1_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"31 March 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MMM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Multimedia Modeling","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bergen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Norway","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":"9 January 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 January 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mmm2023","order":10,"name":"conference_id","label":"Conference ID","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":"Conftool Pro","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"267","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":"86","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":"32% - 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":"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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}