{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T19:08:49Z","timestamp":1743016129353,"version":"3.40.3"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030687861"},{"type":"electronic","value":"9783030687878"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-68787-8_20","type":"book-chapter","created":{"date-parts":[[2021,2,20]],"date-time":"2021-02-20T17:55:55Z","timestamp":1613843755000},"page":"279-291","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Simultaneous Detection of Regular Patterns in Ancient Manuscripts Using GAN-Based Deep Unsupervised Segmentation"],"prefix":"10.1007","author":[{"given":"Milad Omrani","family":"Tamrin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Cheriet","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,2,21]]},"reference":[{"key":"20_CR1","doi-asserted-by":"publisher","first-page":"133738","DOI":"10.1109\/ACCESS.2019.2940884","volume":"7","author":"S Abuelwafa","year":"2019","unstructured":"Abuelwafa, S., Pedersoli, M., Cheriet, M.: Unsupervised exemplar-based learning for improved document image classification. IEEE Access 7, 133738\u2013133748 (2019)","journal-title":"IEEE Access"},{"issue":"11","key":"20_CR2","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., S\u00fcsstrunk, S.: Slic superpixels compared to state-of-the-art superpixel methods. IEEE Trans. Pattern Anal. Mach. Intelli. 34(11), 2274\u20132282 (2012)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intelli."},{"key":"20_CR3","doi-asserted-by":"crossref","unstructured":"Adak, C., Chaudhuri, B.B., Blumenstein, M.: A study on idiosyncratic handwriting with impact on writer identification. In: 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp. 193\u2013198. IEEE (2018)","DOI":"10.1109\/ICFHR-2018.2018.00042"},{"key":"20_CR4","doi-asserted-by":"crossref","unstructured":"Afzal, M.Z., K\u00f6lsch, A., Ahmed, S., Liwicki, M.: Cutting the error by half: investigation of very deep CNN and advanced training strategies for document image classification. In: 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), vol. 1, pp. 883\u2013888. IEEE (2017)","DOI":"10.1109\/ICDAR.2017.149"},{"key":"20_CR5","doi-asserted-by":"crossref","unstructured":"Bousmalis, K., Silberman, N., Dohan, D., Erhan, D., Krishnan, D.: Unsupervised pixel-level domain adaptation with generative adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3722\u20133731 (2017)","DOI":"10.1109\/CVPR.2017.18"},{"key":"20_CR6","doi-asserted-by":"crossref","unstructured":"Bukhari, S.S., Dengel, A.: Visual appearance based document classification methods: Performance evaluation and benchmarking. In: 2015 13th International Conference on Document Analysis and Recognition (ICDAR), pp. 981\u2013985. IEEE (2015)","DOI":"10.1109\/ICDAR.2015.7333908"},{"key":"20_CR7","unstructured":"Chen, S., He, Y., Sun, J., Naoi, S.: Structured document classification by matching local salient features. In: Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), pp. 653\u2013656. IEEE (2012)"},{"key":"20_CR8","unstructured":"Chen, X., Duan, Y., Houthooft, R., Schulman, J., Sutskever, I., Abbeel, P.: Infogan: interpretable representation learning by information maximizing generative adversarial nets. In: Advances in Neural Information Processing Systems, pp. 2172\u20132180 (2016)"},{"key":"20_CR9","doi-asserted-by":"crossref","unstructured":"Das, A., Roy, S., Bhattacharya, U., Parui, S.K.: Document image classification with intra-domain transfer learning and stacked generalization of deep convolutional neural networks. In: 2018 24th International Conference on Pattern Recognition (ICPR), pp. 3180\u20133185. IEEE (2018)","DOI":"10.1109\/ICPR.2018.8545630"},{"key":"20_CR10","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: Imagenet: a large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255. IEEE (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"20_CR11","doi-asserted-by":"crossref","unstructured":"Diem, M., Kleber, F., Fiel, S., Gr\u00fcning, T., Gatos, B.: cbad: ICDAR 2017 competition on baseline detection. In: 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), vol. 1, pp. 1355\u20131360. IEEE (2017)","DOI":"10.1109\/ICDAR.2017.222"},{"key":"20_CR12","unstructured":"Eaton-Rosen, Z., Bragman, F., Ourselin, S., Cardoso, M.J.: Improving data augmentation for medical image segmentation (2018)"},{"key":"20_CR13","doi-asserted-by":"crossref","unstructured":"Gattal, A., Abbas, F., Laouar, M.R.: Automatic parameter tuning of k-means algorithm for document binarization. In: Proceedings of the 7th International Conference on Software Engineering and New Technologies, pp. 1\u20134 (2018)","DOI":"10.1145\/3330089.3330124"},{"key":"20_CR14","unstructured":"Gidaris, S., Singh, P., Komodakis, N.: Unsupervised representation learning by predicting image rotations. arXiv preprint arXiv:1803.07728 (2018)"},{"key":"20_CR15","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems, pp. 2672\u20132680 (2014)"},{"key":"20_CR16","doi-asserted-by":"crossref","unstructured":"Harley, A.W., Ufkes, A., Derpanis, K.G.: Evaluation of deep convolutional nets for document image classification and retrieval. In: 2015 13th International Conference on Document Analysis and Recognition (ICDAR), pp. 991\u2013995. IEEE (2015)","DOI":"10.1109\/ICDAR.2015.7333910"},{"issue":"7","key":"20_CR17","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2006","unstructured":"Hinton, G.E., Osindero, S., Teh, Y.W.: A fast learning algorithm for deep belief nets. Neural Comput. 18(7), 1527\u20131554 (2006)","journal-title":"Neural Comput."},{"key":"20_CR18","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1125\u20131134 (2017)","DOI":"10.1109\/CVPR.2017.632"},{"key":"20_CR19","unstructured":"Ji, B., Chen, T.: Generative adversarial network for handwritten text. arXiv preprint arXiv:1907.11845 (2019)"},{"key":"20_CR20","doi-asserted-by":"crossref","unstructured":"Kanezaki, A.: Unsupervised image segmentation by backpropagation. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1543\u20131547. IEEE (2018)","DOI":"10.1109\/ICASSP.2018.8462533"},{"key":"20_CR21","doi-asserted-by":"crossref","unstructured":"Kumar, J., Doermann, D.: Unsupervised classification of structurally similar document images. In: 2013 12th International Conference on Document Analysis and Recognition, pp. 1225\u20131229. IEEE (2013)","DOI":"10.1109\/ICDAR.2013.248"},{"key":"20_CR22","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431\u20133440 (2015)","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"20_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1007\/978-3-030-13469-3_3","volume-title":"Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications","author":"J Maro\u00f1as","year":"2019","unstructured":"Maro\u00f1as, J., Paredes, R., Ramos, D.: Generative models for deep learning with very scarce data. In: Vera-Rodriguez, R., Fierrez, J., Morales, A. (eds.) CIARP 2018. LNCS, vol. 11401, pp. 20\u201328. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-13469-3_3"},{"key":"20_CR24","doi-asserted-by":"crossref","unstructured":"Ntirogiannis, K., Gatos, B., Pratikakis, I.: ICFHR 2014 competition on handwritten document image binarization (h-dibco 2014). In: 2014 14th International Conference on Frontiers in Handwriting Recognition, pp. 809\u2013813. IEEE (2014)","DOI":"10.1109\/ICFHR.2014.141"},{"key":"20_CR25","doi-asserted-by":"crossref","unstructured":"Pratikakis, I., Zagoris, K., Barlas, G., Gatos, B.: ICDAR 2017 competition on document image binarization (dibco 2017). In: 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), vol. 1, pp. 1395\u20131403. IEEE (2017)","DOI":"10.1109\/ICDAR.2017.228"},{"key":"20_CR26","unstructured":"Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434 (2015)"},{"key":"20_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"key":"20_CR28","doi-asserted-by":"crossref","unstructured":"Saddami, K., Afrah, P., Mutiawani, V., Arnia, F.: A new adaptive thresholding technique for binarizing ancient document. In: 2018 Indonesian Association for Pattern Recognition International Conference (INAPR), pp. 57\u201361. IEEE (2018)","DOI":"10.1109\/INAPR.2018.8627036"},{"key":"20_CR29","doi-asserted-by":"crossref","unstructured":"Schomaker, L.: Lifelong learning for text retrieval and recognition in historical handwritten document collections. arXiv preprint arXiv:1912.05156 (2019)","DOI":"10.1142\/9789811203244_0012"},{"key":"20_CR30","doi-asserted-by":"crossref","unstructured":"Simistira, F., et al.: ICDAR 2017 competition on layout analysis for challenging medieval manuscripts. In: 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), vol. 1, pp. 1361\u20131370. IEEE (2017)","DOI":"10.1109\/ICDAR.2017.223"},{"key":"20_CR31","unstructured":"Tensmeyer, C.A.: Deep learning for document image analysis (2019)"},{"key":"20_CR32","unstructured":"Wei, H., Chen, K., Seuret, M., W\u00fcrsch, M., Liwicki, M., Ingold, R.: Divadiawi-a web-based interface for semi-automatic labeling of historical document images. Digital Humanities (2015)"},{"key":"20_CR33","unstructured":"Xia, X., Kulis, B.: W-net: A deep model for fully unsupervised image segmentation. arXiv preprint arXiv:1711.08506 (2017)"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition. ICPR International Workshops and Challenges"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-68787-8_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,20]],"date-time":"2021-02-20T18:05:03Z","timestamp":1613844303000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-68787-8_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030687861","9783030687878"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-68787-8_20","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"21 February 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 January 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 January 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ICPR2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.icpr2020.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}