{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T06:13:50Z","timestamp":1742969630804,"version":"3.40.3"},"publisher-location":"Cham","reference-count":37,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031216473"},{"type":"electronic","value":"9783031216480"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-21648-0_1","type":"book-chapter","created":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T00:05:14Z","timestamp":1669334714000},"page":"3-17","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Few Shot Multi-representation Approach for\u00a0N-Gram Spotting in\u00a0Historical Manuscripts"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8195-4118","authenticated-orcid":false,"given":"Giuseppe","family":"De Gregorio","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6648-8270","authenticated-orcid":false,"given":"Sanket","family":"Biswas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0100-9392","authenticated-orcid":false,"given":"Mohamed Ali","family":"Souibgui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2405-9811","authenticated-orcid":false,"given":"Asma","family":"Bensalah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4533-4739","authenticated-orcid":false,"given":"Josep","family":"Llad\u00f3s","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9692-5336","authenticated-orcid":false,"given":"Alicia","family":"Forn\u00e9s","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2019-2826","authenticated-orcid":false,"given":"Angelo","family":"Marcelli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,25]]},"reference":[{"key":"1_CR1","doi-asserted-by":"crossref","unstructured":"Almazan, J., Gordo, A., Forn\u00e9s, A., Valveny, E.: Handwritten word spotting with corrected attributes. In: ICCV (2013)","DOI":"10.1109\/ICCV.2013.130"},{"key":"1_CR2","doi-asserted-by":"publisher","first-page":"2552","DOI":"10.1109\/TPAMI.2014.2339814","volume":"36","author":"J Almaz\u00e1n","year":"2014","unstructured":"Almaz\u00e1n, J., Gordo, A., Forn\u00e9s, A., Valveny, E.: Word spotting and recognition with embedded attributes. IEEE TPAMI 36, 2552\u20132566 (2014)","journal-title":"IEEE TPAMI"},{"key":"1_CR3","doi-asserted-by":"crossref","unstructured":"Antonacopoulos, A., Downton, A.C.: Special issue on the analysis of historical documents (2007)","DOI":"10.1007\/s10032-007-0045-1"},{"key":"1_CR4","unstructured":"Bergstra, J., Bengio, Y.: Random search for hyper-parameter optimization. JMLR (2012)"},{"key":"1_CR5","unstructured":"Biswas, S., Banerjee, A., Llad\u00f3s, J., Pal, U.: DocSegTr: an instance-level end-to-end document image segmentation transformer. arXiv preprint arXiv:2201.11438 (2022)"},{"issue":"3","key":"1_CR6","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1007\/s10032-021-00380-6","volume":"24","author":"S Biswas","year":"2021","unstructured":"Biswas, S., Riba, P., Llad\u00f3s, J., Pal, U.: Beyond document object detection: instance-level segmentation of complex layouts. Int. J. Doc. Anal. Recogn. (IJDAR) 24(3), 269\u2013281 (2021)","journal-title":"Int. J. Doc. Anal. Recogn. (IJDAR)"},{"key":"1_CR7","doi-asserted-by":"crossref","unstructured":"Biswas, S., Riba, P., Llad\u00f3s, J., Pal, U.: DocSynth: a layout guided approach for controllable document image synthesis. In: ICDAR (2021)","DOI":"10.1007\/978-3-030-86334-0_36"},{"key":"1_CR8","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1007\/978-1-84628-726-8_8","volume-title":"Digital Document Processing","author":"H Bunke","year":"2007","unstructured":"Bunke, H., Varga, T.: Off-line roman cursive handwriting recognition. In: Chaudhuri, B.B. (ed.) Digital Document Processing, pp. 165\u2013183. Springer, London (2007). https:\/\/doi.org\/10.1007\/978-1-84628-726-8_8"},{"key":"1_CR9","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.procs.2013.05.013","volume":"17","author":"A Choudhary","year":"2013","unstructured":"Choudhary, A., Rishi, R., Ahlawat, S.: A new character segmentation approach for off-line cursive handwritten words. Proc. Comput. Sci. 17, 88\u201395 (2013)","journal-title":"Proc. Comput. Sci."},{"key":"1_CR10","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"1_CR11","doi-asserted-by":"crossref","unstructured":"Howe, N.R.: Part-structured inkball models for one-shot handwritten word spotting. In: ICDAR (2013)","DOI":"10.1109\/ICDAR.2013.121"},{"key":"1_CR12","doi-asserted-by":"crossref","unstructured":"Kang, L., Riba, P., Rusinol, M., Forn\u00e9s, A., Villegas, M.: Distilling content from style for handwritten word recognition. In: ICFHR (2020)","DOI":"10.1109\/ICFHR2020.2020.00035"},{"key":"1_CR13","doi-asserted-by":"crossref","unstructured":"Kang, L., Riba, P., Rusinol, M., Forn\u00e9s, A., Villegas, M.: Content and style aware generation of text-line images for handwriting recognition. IEEE TPAMI (2021)","DOI":"10.1109\/TPAMI.2021.3122572"},{"key":"1_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1007\/978-3-030-58592-1_17","volume-title":"Computer Vision \u2013 ECCV 2020","author":"L Kang","year":"2020","unstructured":"Kang, L., Riba, P., Wang, Y., Rusi\u00f1ol, M., Forn\u00e9s, A., Villegas, M.: GANwriting: content-conditioned generation of styled handwritten word images. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12368, pp. 273\u2013289. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58592-1_17"},{"key":"1_CR15","doi-asserted-by":"publisher","first-page":"963","DOI":"10.1007\/s10044-015-0476-0","volume":"19","author":"T Konidaris","year":"2016","unstructured":"Konidaris, T., Kesidis, A.L., Gatos, B.: A segmentation-free word spotting method for historical printed documents. Pattern Anal. Appl. 19, 963\u2013976 (2016)","journal-title":"Pattern Anal. Appl."},{"key":"1_CR16","doi-asserted-by":"crossref","unstructured":"Kozielski, M., Matysiak, M., Doetsch, P., Schl\u00f6ter, R., Ney, H.: Open-lexicon language modeling combining word and character levels. In: ICFHR (2014)","DOI":"10.1109\/ICFHR.2014.64"},{"key":"1_CR17","doi-asserted-by":"publisher","first-page":"1332","DOI":"10.1126\/science.aab3050","volume":"350","author":"BM Lake","year":"2015","unstructured":"Lake, B.M., Salakhutdinov, R., Tenenbaum, J.B.: Human-level concept learning through probabilistic program induction. Science 350, 1332\u20131338 (2015)","journal-title":"Science"},{"key":"1_CR18","doi-asserted-by":"publisher","first-page":"110","DOI":"10.3390\/jimaging6100110","volume":"6","author":"F Lombardi","year":"2020","unstructured":"Lombardi, F., Marinai, S.: Deep learning for historical document analysis and recognition-a survey. J. Imaging 6, 110 (2020)","journal-title":"J. Imaging"},{"key":"1_CR19","unstructured":"Marcelli, A., Parziale, A., Senatore, R.: Some observations on handwriting from a motor learning perspective. In: AFHA (2013)"},{"key":"1_CR20","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1007\/s100320200071","volume":"5","author":"UV Marti","year":"2002","unstructured":"Marti, U.V., Bunke, H.: The IAM-database: an English sentence database for offline handwriting recognition. IJDAR 5, 39\u201346 (2002)","journal-title":"IJDAR"},{"key":"1_CR21","doi-asserted-by":"publisher","first-page":"109","DOI":"10.3390\/jimaging6100109","volume":"6","author":"A Parziale","year":"2020","unstructured":"Parziale, A., Capriolo, G., Marcelli, A.: One step is not enough: a multi-step procedure for building the training set of a query by string keyword spotting system to assist the transcription of historical document. J. Imaging 6, 109 (2020)","journal-title":"J. Imaging"},{"key":"1_CR22","doi-asserted-by":"crossref","unstructured":"Poznanski, A., Wolf, L.: CNN-N-gram for handwriting word recognition. In: CVPR (2016)","DOI":"10.1109\/CVPR.2016.253"},{"key":"1_CR23","doi-asserted-by":"publisher","first-page":"2373","DOI":"10.1007\/s00521-016-2197-8","volume":"28","author":"J Puigcerver","year":"2017","unstructured":"Puigcerver, J., Toselli, A.H., Vidal, E.: Querying out-of-vocabulary words in lexicon-based keyword spotting. Neural Comput. Appl. 28, 2373\u20132382 (2017)","journal-title":"Neural Comput. Appl."},{"key":"1_CR24","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1007\/s10032-006-0027-8","volume":"9","author":"TM Rath","year":"2007","unstructured":"Rath, T.M., Manmatha, R.: Word spotting for historical documents. IJDAR 9, 139\u2013152 (2007)","journal-title":"IJDAR"},{"key":"1_CR25","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. In: NeurIPS (2015)"},{"key":"1_CR26","doi-asserted-by":"crossref","unstructured":"Sanchez, J.A., Toselli, A.H., Romero, V., Vidal, E.: ICDAR 2015 competition HTRtS: Handwritten text recognition on the transcriptorium dataset. In: ICDAR (2015)","DOI":"10.1109\/ICDAR.2015.7333944"},{"key":"1_CR27","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1016\/S0031-3203(99)00055-2","volume":"33","author":"J Sauvola","year":"2000","unstructured":"Sauvola, J., Pietik\u00e4inen, M.: Adaptive document image binarization. Pattern Recogn. 33, 225\u2013236 (2000)","journal-title":"Pattern Recogn."},{"key":"1_CR28","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1007\/978-3-030-82269-9_16","volume-title":"Applied Intelligence and Informatics","author":"N Shaffi","year":"2021","unstructured":"Shaffi, N., Hajamohideen, F.: Few-shot learning for Tamil handwritten character recognition using deep Siamese convolutional neural network. In: Mahmud, M., Kaiser, M.S., Kasabov, N., Iftekharuddin, K., Zhong, N. (eds.) AII 2021. CCIS, vol. 1435, pp. 204\u2013215. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-82269-9_16"},{"key":"1_CR29","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)"},{"key":"1_CR30","doi-asserted-by":"crossref","unstructured":"Souibgui, M.A., Forn\u00e9s, A., Kessentini, Y., Tudor, C.: A few-shot learning approach for historical ciphered manuscript recognition. In: ICPR (2021)","DOI":"10.1109\/ICPR48806.2021.9413255"},{"key":"1_CR31","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1016\/j.patcog.2018.04.001","volume":"81","author":"M Stauffer","year":"2018","unstructured":"Stauffer, M., Fischer, A., Riesen, K.: Keyword spotting in historical handwritten documents based on graph matching. Pattern Recogn. 81, 240\u2013253 (2018)","journal-title":"Pattern Recogn."},{"key":"1_CR32","doi-asserted-by":"crossref","unstructured":"Sudholt, S., Fink, G.A.: PHOCNet: a deep convolutional neural network for word spotting in handwritten documents. In: ICFHR (2016)","DOI":"10.1109\/ICFHR.2016.0060"},{"key":"1_CR33","doi-asserted-by":"publisher","first-page":"1043","DOI":"10.1016\/S0167-8655(01)00042-3","volume":"22","author":"A Vinciarelli","year":"2001","unstructured":"Vinciarelli, A., Luettin, J.: A new normalization technique for cursive handwritten words. Pattern Recogn. Lett. 22, 1043\u20131050 (2001)","journal-title":"Pattern Recogn. Lett."},{"key":"1_CR34","unstructured":"Vinyals, O., Blundell, C., Lillicrap, T., Wierstra, D., et al.: Matching networks for one shot learning. In: NeurIPS (2016)"},{"key":"1_CR35","doi-asserted-by":"publisher","first-page":"821","DOI":"10.1016\/j.patrec.2019.08.005","volume":"125","author":"T Wang","year":"2019","unstructured":"Wang, T., Xie, Z., Li, Z., Jin, L., Chen, X.: Radical aggregation network for few-shot offline handwritten Chinese character recognition. Pattern Recogn. Lett. 125, 821\u2013827 (2019)","journal-title":"Pattern Recogn. Lett."},{"key":"1_CR36","first-page":"1","volume":"53","author":"Y Wang","year":"2020","unstructured":"Wang, Y., Yao, Q., Kwok, J.T., Ni, L.M.: Generalizing from a few examples: a survey on few-shot learning. ACM Comput. Surv. (CSUR) 53, 1\u201334 (2020)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"1_CR37","doi-asserted-by":"crossref","unstructured":"Wong, A., Yuille, A.L.: One shot learning via compositions of meaningful patches. In: ICCV (2015)","DOI":"10.1109\/ICCV.2015.142"}],"container-title":["Lecture Notes in Computer Science","Frontiers in Handwriting Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-21648-0_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T14:42:50Z","timestamp":1710340970000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-21648-0_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031216473","9783031216480"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-21648-0_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"25 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICFHR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Frontiers in Handwriting Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hyderabad","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 December 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 December 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icfhr2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/icfhr2022.org","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":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"61","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":"36","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":"1","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":"59% - 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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}