{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T17:09:58Z","timestamp":1779296998797,"version":"3.51.4"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2021,9,18]],"date-time":"2021-09-18T00:00:00Z","timestamp":1631923200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,9,18]],"date-time":"2021-09-18T00:00:00Z","timestamp":1631923200000},"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":["Memetic Comp."],"published-print":{"date-parts":[[2021,12]]},"DOI":"10.1007\/s12293-021-00345-6","type":"journal-article","created":{"date-parts":[[2021,9,18]],"date-time":"2021-09-18T03:02:31Z","timestamp":1631934151000},"page":"459-475","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Multi-lingual character handwriting framework based on an integrated deep learning based sequence-to-sequence attention model"],"prefix":"10.1007","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2964-4363","authenticated-orcid":false,"given":"Besma","family":"Rabhi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdelkarim","family":"Elbaati","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Houcine","family":"Boubaker","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yahia","family":"Hamdi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amir","family":"Hussain","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adel M.","family":"Alimi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,9,18]]},"reference":[{"key":"345_CR1","unstructured":"Bahdanau D, Cho K, Bengio Y (2014) Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473"},{"key":"345_CR2","doi-asserted-by":"crossref","unstructured":"Bhunia AK, Bhowmick A, Bhunia AK, Konwer A, Banerjee P, Roy PP, Pal U (2018) Handwriting trajectory recovery using end-to-end deep encoder-decoder network. In: 2018 24th international conference on pattern recognition (ICPR). IEEE, pp 3639\u20133644","DOI":"10.1109\/ICPR.2018.8546093"},{"key":"345_CR3","doi-asserted-by":"crossref","unstructured":"Sumi T, Iwana BK, Hayashi H, Uchida S (2019) Modality conversion of handwritten patterns by cross variational autoencoders. In: 2019 international conference on document analysis and recognition (ICDAR), pp 407\u2013412","DOI":"10.1109\/ICDAR.2019.00072"},{"key":"345_CR4","unstructured":"Nguyen HT, Nakamura T, Nguyen CT, Nakagawa M (2020) Online trajectory recovery from offline handwritten Japanese kanji characters of multiple strokes. In: 25th international conference on pattern recognition (ICPR). IEEE"},{"key":"345_CR5","unstructured":"Chung J, Gulcehre C, Cho K, Bengio Y (2014) Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555"},{"key":"345_CR6","doi-asserted-by":"crossref","unstructured":"Crispo G, Diaz M, Marcelli A, Ferrer M A (2018) Tracking the ballistic trajectory in complex and long handwritten signatures. In: 2018 16th international conference on frontiers in handwriting recognition (ICFHR). IEEE, pp 351\u2013356","DOI":"10.1109\/ICFHR-2018.2018.00068"},{"key":"345_CR7","doi-asserted-by":"publisher","first-page":"352","DOI":"10.1016\/j.eswa.2016.08.017","volume":"64","author":"M Dinh","year":"2016","unstructured":"Dinh M, Yang HJ, Lee GS, Kim SH, Do LN (2016) Recovery of drawing order from multi-stroke English handwritten images based on graph models and ambiguous zone analysis. Expert Syst Appl 64:352\u2013364","journal-title":"Expert Syst Appl"},{"key":"345_CR8","doi-asserted-by":"publisher","unstructured":"Faundez-Zanuy M, Fierrez J, Ferrer MA et al (2020) Handwriting biometrics: applications and future trends in e-security and e-health. Cogn Comput 12:940\u2013953. https:\/\/doi.org\/10.1007\/s12559-020-09755-z","DOI":"10.1007\/s12559-020-09755-z"},{"key":"345_CR9","doi-asserted-by":"crossref","unstructured":"Elbaati A, Kherallah M, Ennaji A, Alimi AM (2009) Temporal order recovery of the scanned handwriting. In: 2009 10th international conference on document analysis and recognition. IEEE, pp 1116\u20131120","DOI":"10.1109\/ICDAR.2009.266"},{"key":"345_CR10","doi-asserted-by":"crossref","unstructured":"Hamdi Y, Boubaker H, Dhieb T, Elbaati A, Alimi AM (2019) Hybrid DBLSTM-SVM based beta-elliptic-CNN models for online Arabic characters recognition. In: 2019 international conference on document analysis and recognition (ICDAR). IEEE, pp 545\u2013550","DOI":"10.1109\/ICDAR.2019.00093"},{"key":"345_CR11","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"345_CR12","doi-asserted-by":"crossref","unstructured":"Diaz M, Crispo G, Parziale A, Marcelli A, Ferrer MA (2021) Writing order recovery in complex and long static handwriting. In: International journal of interactive multimedia and artificial intelligence","DOI":"10.9781\/ijimai.2021.04.003"},{"issue":"8","key":"345_CR13","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735\u20131780","journal-title":"Neural Comput"},{"key":"345_CR14","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1016\/j.neunet.2019.12.006","volume":"123","author":"C Ieracitano","year":"2020","unstructured":"Ieracitano C, Mammone N, HussainA MFC (2020) A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia. Neural Netw 123:176\u2013190","journal-title":"Neural Netw"},{"key":"345_CR15","doi-asserted-by":"publisher","unstructured":"Gorban AN, Mirkes EM, Tyukin IY (2020) How deep should be the depth of convolutional neural networks: a backyard dog case study. Cogn Comput 12:388\u2013397. https:\/\/doi.org\/10.1007\/s12559-019-09667-7","DOI":"10.1007\/s12559-019-09667-7"},{"key":"345_CR16","unstructured":"Kherallah M, Elbaati A, Abed HE, Alimi AM (2008) The on\/off (LMCA) dual Arabic handwriting database. In: 11th international conference on frontiers in handwriting recognition (ICFHR)"},{"issue":"11","key":"345_CR17","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun Y, Bottou L, Bengio Y, Haffner P (1998) Gradient-based learning applied to document recognition. Proc IEEE 86(11):2278\u20132324","journal-title":"Proc IEEE"},{"issue":"6","key":"345_CR18","doi-asserted-by":"publisher","first-page":"2063","DOI":"10.1109\/TNNLS.2018.2790388","volume":"29","author":"M Mahmud","year":"2018","unstructured":"Mahmud M, Kaiser MS, Hussain A, Vassanelli S (2018) Applications of deep learning and reinforcement learning to biological data. IEEE Trans Neural Netw Learn Syst 29(6):2063\u20132079","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"345_CR19","doi-asserted-by":"publisher","unstructured":"Rabhi B, Elbaati A, Hamdani TM, Alimi AM (2021) ASAR 2021 competition on online signal restoration using arabic handwriting Dhad dataset. In: Barney Smith EH, Pal U (eds) Document analysis and recognition \u2013 ICDAR 2021 workshops. ICDAR 2021. Lecture Notes in Computer Science, vol 12916. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-030-86198-8_26","DOI":"10.1007\/978-3-030-86198-8_26"},{"issue":"1","key":"345_CR20","first-page":"358","volume":"9","author":"D Phan","year":"2015","unstructured":"Phan D, Na IS, Kim SH, Lee GS, Yang HJ (2015) triangulation based skeletonization and trajectory recovery for handwritten character patterns. KSII Trans Internet Inf Syst 9(1):358\u2013377","journal-title":"KSII Trans Internet Inf Syst"},{"issue":"11","key":"345_CR21","doi-asserted-by":"publisher","first-page":"1724","DOI":"10.1109\/TPAMI.2006.216","volume":"28","author":"Y Qiao","year":"2006","unstructured":"Qiao Y, Nishiara M, Yasuhara M (2006) A framework toward restoration of writing order from single-stroked handwriting image. IEEE Trans Pattern Anal Mach Intell 28(11):1724\u20131737","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"345_CR22","doi-asserted-by":"crossref","unstructured":"Rabhi B, Elbaati A, Hamdi Y, Alimi AM (2019) Handwriting recognition based on temporal order restored by the end-to-end system. In: 2019 international conference on document analysis and recognition (ICDAR). IEEE, pp 1231\u20131236","DOI":"10.1109\/ICDAR.2019.00199"},{"key":"345_CR23","doi-asserted-by":"crossref","unstructured":"Rabhi B, Dhahri H, Alimi AM, Alturki FA (2016) Grey wolf optimizer for training Elman neural network. In: International conference on hybrid intelligent systems. Springer, Cham, pp 380\u2013390","DOI":"10.1007\/978-3-319-52941-7_38"},{"key":"345_CR24","doi-asserted-by":"crossref","unstructured":"Rousseau L, Anquetil E, Camillerapp J (2005) Recovery of a drawing order from off-line isolated letters dedicated to on-line recognition. In: 8th international conference on document analysis and recognition (ICDAR'05). IEEE, pp 1121\u20131125","DOI":"10.1109\/ICDAR.2005.199"},{"key":"345_CR25","unstructured":"Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556"},{"issue":"2","key":"345_CR26","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1109\/TPAMI.2008.68","volume":"31","author":"T Steinherz","year":"2008","unstructured":"Steinherz T, Doermann D, Rivlin E, Intrator N (2008) Offline loop investigation for handwriting analysis. IEEE Trans Pattern Anal Mach Intell 31(2):193\u2013209","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"345_CR27","doi-asserted-by":"crossref","unstructured":"Viard-Gaudin C, Lallican PM, Knerr S, Binter P (1999) The ireste on\/off (ironoff) dual handwriting database. In: Proceedings of the 5th international conference on document analysis and recognition. ICDAR'99 (Cat. No. PR00318). IEEE, pp 455\u2013458","DOI":"10.1109\/ICDAR.1999.791823"},{"issue":"1","key":"345_CR28","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1109\/TSMC.2018.2800040","volume":"49","author":"F Xiong","year":"2018","unstructured":"Xiong F, Sun B, Yang X, Qiao H, Huang K, Hussain A, Liu Z (2018) Guided policy search for sequential multitask learning. IEEE Trans Syst, Man, Cybern: Syst 49(1):216\u2013226","journal-title":"IEEE Trans Syst, Man, Cybern: Syst"},{"key":"345_CR29","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1007\/s12293-020-00310-9","volume":"12","author":"S Sadeg","year":"2020","unstructured":"Sadeg S, Hamdad L, Chettab H et al (2020) Feature selection based bee swarm meta-heuristic approach for combinatorial optimisation problems: a case-study on MaxSAT. Memet Comput 12:283\u2013298. https:\/\/doi.org\/10.1007\/s12293-020-00310-9","journal-title":"Memet Comput"},{"key":"345_CR30","doi-asserted-by":"publisher","DOI":"10.1007\/s12293-021-00339-4","author":"T Wang","year":"2021","unstructured":"Wang T, Peng X, Jin Y et al (2021) Experience sharing based memetic transfer learning for multiagent reinforcement learning. Memet Comput. https:\/\/doi.org\/10.1007\/s12293-021-00339-4","journal-title":"Memet Comput"}],"container-title":["Memetic Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12293-021-00345-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12293-021-00345-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12293-021-00345-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T10:11:34Z","timestamp":1637143894000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12293-021-00345-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,18]]},"references-count":30,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["345"],"URL":"https:\/\/doi.org\/10.1007\/s12293-021-00345-6","relation":{"has-preprint":[{"id-type":"doi","id":"10.36227\/techrxiv.13902650.v2","asserted-by":"object"},{"id-type":"doi","id":"10.36227\/techrxiv.13902650.v1","asserted-by":"object"}]},"ISSN":["1865-9284","1865-9292"],"issn-type":[{"value":"1865-9284","type":"print"},{"value":"1865-9292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,18]]},"assertion":[{"value":"14 February 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 September 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 September 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}}]}}