{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T10:21:20Z","timestamp":1785406880458,"version":"3.56.0"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2018,5,30]],"date-time":"2018-05-30T00:00:00Z","timestamp":1527638400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001665","name":"Agence Nationale de la Recherche","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["IJDAR"],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1007\/s10032-018-0304-3","type":"journal-article","created":{"date-parts":[[2018,5,30]],"date-time":"2018-05-30T09:56:16Z","timestamp":1527674176000},"page":"177-186","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":75,"title":["Fully convolutional network with dilated convolutions for handwritten text line segmentation"],"prefix":"10.1007","volume":"21","author":[{"given":"Guillaume","family":"Renton","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yann","family":"Soullard","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cl\u00e9ment","family":"Chatelain","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S\u00e9bastien","family":"Adam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Kermorvant","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thierry","family":"Paquet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2018,5,30]]},"reference":[{"key":"304_CR1","unstructured":"Badrinarayanan, V., Kendall, A., Cipolla, R.: Segnet: A deep convolutional encoder\u2013decoder architecture for image segmentation (2015). \n                    arXiv:1511.00561"},{"key":"304_CR2","unstructured":"Chen, L., Papandreou, V., Kokkinos, I., Murphy, K., Yuille, A.: Semantic image segmentation with deep convolutional nets and fully connected crfs (2014). \n                    arXiv:1412.7062"},{"key":"304_CR3","unstructured":"Chen, LC., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Deeplab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs (2016). \n                    arXiv:1606.00915"},{"key":"304_CR4","unstructured":"Chen, LC., Papandreou, G., Schroff, F., Adam, H.: Rethinking atrous convolution for semantic image segmentation (2017). \n                    arXiv:1706.05587"},{"key":"304_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.patcog.2016.10.023","volume":"64","author":"S Eskenazi","year":"2017","unstructured":"Eskenazi, S., Gomez-Kr\u00e4mer, P., Ogier, J.M.: A comprehensive survey of mostly textual document segmentation algorithms since 2008. Pattern Recognit. 64, 1\u201314 (2017)","journal-title":"Pattern Recognit."},{"key":"304_CR6","doi-asserted-by":"crossref","unstructured":"Girshick, R.: Fast r-cnn. In: ICCV, pp. 1440\u20131448 (2015)","DOI":"10.1109\/ICCV.2015.169"},{"key":"304_CR7","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: CVPR, pp. 580\u2013587 (2014)","DOI":"10.1109\/CVPR.2014.81"},{"key":"304_CR8","unstructured":"Gr\u00fcning, T., Labahn, R., Diem, M., Kleber, F., Fiel, S.: Read-bad: a new dataset and evaluation scheme for baseline detection in archival documents (2017). \n                    arXiv:1705.03311"},{"key":"304_CR9","doi-asserted-by":"crossref","unstructured":"Holschneider, M., Kronland-Martinet, R., Morlet, J., Tchamitchian, P.: A real-time algorithm for signal analysis with the help of the wavelet transform. In: Wavelets, pp. 286\u2013297. Springer (1989)","DOI":"10.1007\/978-3-642-97177-8_28"},{"key":"304_CR10","doi-asserted-by":"crossref","unstructured":"Huang, W., Qiao, Y., Tang, X.: Robust scene text detection with convolution neural network induced mser trees. In: ECCV, pp. 497\u2013511 (2014)","DOI":"10.1007\/978-3-319-10593-2_33"},{"key":"304_CR11","unstructured":"Kr\u00e4henb\u00fchl, P.: Koltun, V.: Efficient inference in fully connected CRFs with gaussian edge potentials. In: NIPS, pp. 109\u2013117 (2011)"},{"issue":"7553","key":"304_CR12","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436\u2013444 (2015)","journal-title":"Nature"},{"key":"304_CR13","doi-asserted-by":"crossref","unstructured":"Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C., Berg, A.: Ssd: Single shot multibox detector. In: ECCV, pp. 21\u201337. Springer (2016)","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"304_CR14","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: CVPR, pp. 3431\u20133440 (2015)","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"304_CR15","doi-asserted-by":"crossref","unstructured":"Moysset, B., Adam, P., Wolf, C., Louradour, J.: Space displacement localization neural networks to locate origin points of handwritten text lines in historical documents. In: Workshop on Historical Document Imaging and Processing, August (2015)","DOI":"10.1145\/2809544.2809546"},{"key":"304_CR16","doi-asserted-by":"crossref","unstructured":"Moysset, B., Kermorvant, C., Wolf, C.: Full-page text recognition: learning where to start and when to stop. In: ICDAR (2017)","DOI":"10.1109\/ICDAR.2017.147"},{"key":"304_CR17","doi-asserted-by":"crossref","unstructured":"Moysset, B., Kermorvant, C., Wolf, C., Louradour, J.: Paragraph text segmentation into lines with recurrent neural networks. In: ICDAR, pp. 456\u2013460 (2015)","DOI":"10.1109\/ICDAR.2015.7333803"},{"key":"304_CR18","doi-asserted-by":"crossref","unstructured":"Moysset, B., Louradour, J., Kermorvant, C., Wolf, C.: Learning text-line localization with shared and local regression neural networks. In: ICFHR (2016)","DOI":"10.1109\/ICFHR.2016.0014"},{"key":"304_CR19","unstructured":"Murdock, M., Reid, S., Hamilton, B., Reese, J.: Icdar 2015 competition on text line detection in historical documents. In: ICDAR, pp, 1171\u20131175 (2015)"},{"key":"304_CR20","doi-asserted-by":"crossref","unstructured":"Noh, H., Hong, S., Han, B.: Learning deconvolution network for semantic segmentation. In: ICCV, pp. 1520\u20131528 (2015)","DOI":"10.1109\/ICCV.2015.178"},{"issue":"4","key":"304_CR21","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1007\/s10032-011-0173-5","volume":"15","author":"T Paquet","year":"2012","unstructured":"Paquet, T., Heutte, L., Koch, G., Chatelain, C.: A categorization system for handwritten documents. IJDAR 15(4), 315\u2013330 (2012)","journal-title":"IJDAR"},{"issue":"2","key":"304_CR22","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1145\/2431211.2431222","volume":"45","author":"MT Parvez","year":"2013","unstructured":"Parvez, M.T., Mahmoud, S.A.: Offline arabic handwritten text recognition: a survey. ACM Comput. Surv. (CSUR) 45(2), 23 (2013)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"304_CR23","unstructured":"Peng, C., Zhang, X., Yu, G., Luo, G., Sun, J.: Large kernel matters\u2014improve semantic segmentation by global convolutional network (2017). \n                    arXiv:1703.02719"},{"key":"304_CR24","doi-asserted-by":"crossref","unstructured":"Redmon, J., Farhadi, A.: YOLO9000: better, faster, stronger. CoRR, abs\/1612.08242 (2016)","DOI":"10.1109\/CVPR.2017.690"},{"key":"304_CR25","doi-asserted-by":"crossref","unstructured":"Renton, G., Chatelain, C., Adam, S., Kermorvant, C., Paquet, T.: Handwritten text line segmentation using fully convolutional network. In 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), 2017, vol.\u00a05, pp. 5\u20139. IEEE (2017)","DOI":"10.1109\/ICDAR.2017.321"},{"key":"304_CR26","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. CoRR, abs\/1505.04597 (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"issue":"9","key":"304_CR27","doi-asserted-by":"publisher","first-page":"1115","DOI":"10.1109\/LSP.2014.2325940","volume":"21","author":"J Ryu","year":"2014","unstructured":"Ryu, J., Koo, H.I., Cho, N.I.: Language-independent text-line extraction algorithm for handwritten documents. Signal Process. Lett. 21(9), 1115\u20131119 (2014)","journal-title":"Signal Process. Lett."},{"key":"304_CR28","doi-asserted-by":"crossref","unstructured":"Shi, Z., Setlur, S., Govindaraju, V.: A steerable directional local profile technique for extraction of handwritten arabic text lines. In: ICDAR, pp. 176\u2013180 (2009)","DOI":"10.1109\/ICDAR.2009.79"},{"key":"304_CR29","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. CoRR, abs\/1409.1556 (2014)"},{"key":"304_CR30","doi-asserted-by":"crossref","unstructured":"Stamatopoulos, N., Gatos, B., Louloudis, G., Pal, U., Alaei, A.: Icdar 2013 handwriting segmentation contest. In: ICDAR, pp. 1402\u20131406 (2013)","DOI":"10.1109\/ICDAR.2013.283"},{"key":"304_CR31","unstructured":"Stuner, B., Chatelain, C., Paquet, T.: LV-ROVER: lexicon verified recognizer output voting error reduction. CoRR, abs\/1707.07432 (2017)"},{"key":"304_CR32","doi-asserted-by":"crossref","unstructured":"Vo, Q.N., Lee, G.: Dense prediction for text line segmentation in handwritten document images. In: ICIP, pp. 3264\u20133268 (2016)","DOI":"10.1109\/ICIP.2016.7532963"},{"key":"304_CR33","unstructured":"Yu, F., Koltun, V.: Multi-scale context aggregation by dilated convolutions (2015). \n                    arXiv:1511.07122"},{"key":"304_CR34","unstructured":"Zhang, Z., Zhang, C., Shen, W., Yao, C., Liu, W., Bai, X.: Multi-oriented text detection with fully convolutional networks (2016). \n                    arXiv:1604.04018"},{"key":"304_CR35","doi-asserted-by":"crossref","unstructured":"Zheng, S., Jayasumana, S., Romera-Paredes, B., Vineet, V., Su, Z., Du, D., Huang, C., Torr, P.: Conditional random fields as recurrent neural networks. In: ICCV, pp. 1529\u20131537 (2015)","DOI":"10.1109\/ICCV.2015.179"},{"key":"304_CR36","doi-asserted-by":"crossref","unstructured":"Zhu, S., Zanibbi, R.: A text detection system for natural scenes with convolutional feature learning and cascaded classification. In: CVPR, pp. 625\u2013632 (2016)","DOI":"10.1109\/CVPR.2016.74"}],"container-title":["International Journal on Document Analysis and Recognition (IJDAR)"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10032-018-0304-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10032-018-0304-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10032-018-0304-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,29]],"date-time":"2019-05-29T19:10:16Z","timestamp":1559157016000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10032-018-0304-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5,30]]},"references-count":36,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2018,9]]}},"alternative-id":["304"],"URL":"https:\/\/doi.org\/10.1007\/s10032-018-0304-3","relation":{},"ISSN":["1433-2833","1433-2825"],"issn-type":[{"value":"1433-2833","type":"print"},{"value":"1433-2825","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,5,30]]},"assertion":[{"value":"29 September 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 May 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 May 2018","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 May 2018","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}