{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T19:05:12Z","timestamp":1785697512929,"version":"3.56.0"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,11,23]],"date-time":"2024-11-23T00:00:00Z","timestamp":1732320000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,23]],"date-time":"2024-11-23T00:00:00Z","timestamp":1732320000000},"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":["Cogn Comput"],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1007\/s12559-024-10382-1","type":"journal-article","created":{"date-parts":[[2024,11,23]],"date-time":"2024-11-23T02:39:05Z","timestamp":1732329545000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Novel Multi-head Attention and Long Short-Term Network for Enhanced Inpainting of Occluded Handwriting"],"prefix":"10.1007","volume":"17","author":[{"given":"Besma","family":"Rabhi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdelkarim","family":"Elbaati","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yahia","family":"Hamdi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Habib","family":"Dhahri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Umapada","family":"Pal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Habib","family":"Chabchoub","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Khmaies","family":"Ouahada","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adel M.","family":"Alimi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,11,23]]},"reference":[{"key":"10382_CR1","doi-asserted-by":"publisher","first-page":"111392","DOI":"10.1016\/j.asoc.2024.111392","volume":"154","author":"Y Chen","year":"2024","unstructured":"Chen Y, Xia R, Yang K, Zou K. DNNAM: image inpainting algorithm via deep neural networks and attention mechanism. Appl Soft Comput. 2024;154:111392.","journal-title":"Appl Soft Comput"},{"key":"10382_CR2","doi-asserted-by":"crossref","unstructured":"Chan TF, Shen J, Zhou HM. A total variation wavelet inpainting model with multilevel fitting parameters. In: Advanced signal processing algorithms, architectures, and implementations XVI, vol. 6313. SPIE; 2006. pp. 108\u201315.","DOI":"10.1117\/12.682222"},{"key":"10382_CR3","doi-asserted-by":"publisher","unstructured":"Arias P, Caselles V, Sapiro GA. Variational framework for non-local image inpainting. Proc. EMMCVPR'09. 2009;345\u2013358.\u00a0https:\/\/doi.org\/10.1007\/978-3-642-03641-5_26","DOI":"10.1007\/978-3-642-03641-5_26"},{"key":"10382_CR4","unstructured":"Shibata T, Iketani A, Senda Sh. Fast and structure-preserving inpainting based on probabilistic structure estimation. In: MVA 2011 IAPR conference on machine vision applications. Nara, JAPAN; 2011. pp. 22\u201325."},{"key":"10382_CR5","doi-asserted-by":"crossref","unstructured":"Potapov A, Scherbakov O, Zhdanov I. Practical algorithmic probability: an image inpainting example. In Sixth International Conference on Machine Vision (ICMV 2013). 2013;(9067):240\u2013244. SPIE.","DOI":"10.1117\/12.2051405"},{"issue":"4","key":"10382_CR6","first-page":"1","volume":"33","author":"JB Huang","year":"2014","unstructured":"Huang JB, Kang SB, Ahuja N, Kopf J. Image completion using planar structure guidance. ACM Transactions on graphics (TOG). 2014;33(4):1\u201310.","journal-title":"ACM Transactions on graphics (TOG)"},{"issue":"9","key":"10382_CR7","doi-asserted-by":"publisher","first-page":"2117","DOI":"10.1109\/TPAMI.2012.271","volume":"35","author":"Y Hu","year":"2012","unstructured":"Hu Y, Zhang D, Ye J, Li X, He X. Fast and accurate matrix completion via truncated nuclear norm regularization. IEEE Trans Pattern Anal Mach Intell. 2012;35(9):2117\u201330.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"2","key":"10382_CR8","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1007\/s10044-012-0316-4","volume":"17","author":"A Sai Hareesh","year":"2014","unstructured":"Sai Hareesh A, Chandrasekaran V. Exemplar-based color image inpainting: a fractional gradient function approach. Pattern Anal Appl. 2014;17(2):389\u201399.","journal-title":"Pattern Anal Appl"},{"key":"10382_CR9","doi-asserted-by":"publisher","unstructured":"Xi X, Wang F, Liu Y. Improved Criminisi algorithm based on a new priority function with the gray entropy. Ninth Int Conf Comput Intell Secur. 2013;2013214\u2013218, https:\/\/doi.org\/10.1109\/CIS.2013.52.","DOI":"10.1109\/CIS.2013.52"},{"key":"10382_CR10","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1016\/j.neucom.2020.07.046","volume":"415","author":"G Song","year":"2020","unstructured":"Song G, Li J, Wang Z. Occluded offline handwritten Chinese character inpainting via generative adversarial network and self-attention mechanism. Neurocomputing. 2020;415:146\u201356.","journal-title":"Neurocomputing"},{"issue":"11","key":"10382_CR11","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. Gradient-based learning applied to document recognition. Proc IEEE. 1998;86(11):2278\u2013324.","journal-title":"Proc IEEE"},{"key":"10382_CR12","doi-asserted-by":"crossref","unstructured":"Pathak D, Krahenbuhl P, Donahue J, Darrell T, Efros AA. Context encoders: feature learning by inpainting. In: Proceedings of the IEEE conference on computer vision and pattern recognition. 2016. pp. 2536\u201344.","DOI":"10.1109\/CVPR.2016.278"},{"key":"10382_CR13","unstructured":"Xie J, Xu L, Chen E. Image denoising and inpainting with deep neural networks.\u00a0Adv Neural Inf Process Syst. 2012;25."},{"key":"10382_CR14","doi-asserted-by":"publisher","unstructured":"Rabhi B, Elbaati A, Boubaker H, et al. Temporal order and pen velocity recovery for character handwriting based on sequence-to-sequence with attention mode. TechRxiv. February 12, 2021. https:\/\/doi.org\/10.36227\/techrxiv.13902650.v1","DOI":"10.36227\/techrxiv.13902650.v1"},{"key":"10382_CR15","doi-asserted-by":"crossref","unstructured":"Shcherbakov O, Batishcheva V. Image inpainting based on stacked autoencoders. In Journal of Physics: Conference Series. 2014;536(1):012020. IOP Publishing.","DOI":"10.1088\/1742-6596\/536\/1\/012020"},{"issue":"1","key":"10382_CR16","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1109\/TIP.2007.911828","volume":"17","author":"J Mairal","year":"2007","unstructured":"Mairal J, Elad M, Sapiro G. Sparse representation for color image restoration. IEEE Trans Image Process. 2007;17(1):53\u201369.","journal-title":"IEEE Trans Image Process"},{"key":"10382_CR17","unstructured":"Xu L, Ren JS, Liu C, Jia J. Deep convolutional neural network for image deconvolution. Adv Neural Inf Process Syst. 2014;27."},{"issue":"4","key":"10382_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3072959.3073659","volume":"36","author":"S Iizuka","year":"2017","unstructured":"Iizuka S, Simo-Serra E, Ishikawa H. Globally and locally consistent image completion. ACM Trans Graphics (ToG). 2017;36(4):1\u201314.","journal-title":"ACM Trans Graphics (ToG)"},{"issue":"9","key":"10382_CR19","doi-asserted-by":"publisher","first-page":"4805","DOI":"10.1007\/s00521-018-3854-x","volume":"32","author":"J Li","year":"2020","unstructured":"Li J, Song G, Zhang M. Occluded offline handwritten Chinese character recognition using deep convolutional generative adversarial network and improved GoogLeNet. Neural Comput Appl. 2020;32(9):4805\u201319.","journal-title":"Neural Comput Appl"},{"key":"10382_CR20","doi-asserted-by":"crossref","unstructured":"Yuan K, Guo S, Liu Z, Zhou A, Yu F, Wu W. Incorporating convolution designs into visual transformers. In: Proceedings of the IEEE\/CVF international conference on computer vision. 2021. pp. 579\u201388.","DOI":"10.1109\/ICCV48922.2021.00062"},{"key":"10382_CR21","doi-asserted-by":"publisher","unstructured":"Hamdi Y, Boubaker H, Rabhi B, Ouarda W, Alimi AM. Hybrid architecture based on RNN-SVM for multilingual online handwriting recognition using beta-elliptic and CNN models. 2021. TechRxiv. Preprint. https:\/\/doi.org\/10.36227\/techrxiv.13903661.v3.","DOI":"10.36227\/techrxiv.13903661.v3"},{"key":"10382_CR22","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1007\/s12293-021-00345-6","volume":"13","author":"B Rabhi","year":"2021","unstructured":"Rabhi B, Elbaati A, Boubaker H, Hamdi Y, Hussain A, Alimi AM. Multi-lingual character handwriting framework based on an integrated deep learning based sequence-to-sequence attention model. Memetic Computing. 2021;13:459\u201375. https:\/\/doi.org\/10.1007\/s12293-021-00345-6.","journal-title":"Memetic Computing"},{"key":"10382_CR23","doi-asserted-by":"publisher","unstructured":"Rabhi B, Elbaati A, Hamdi Y, Alimi A. Handwriting recognition based on temporal order restored by the end-to-end system. International Conference on Document Analysis and Recognition (ICDAR), Sydney, NSW, Australia. 2019;1231\u20131236. https:\/\/doi.org\/10.1109\/ICDAR.2019.00199","DOI":"10.1109\/ICDAR.2019.00199"},{"issue":"8","key":"10382_CR24","doi-asserted-by":"publisher","first-page":"22295","DOI":"10.1007\/s11042-023-16499-z","volume":"83","author":"B Rabhi","year":"2024","unstructured":"Rabhi B, Elbaati A, Boubaker H, Pal U, Alimi AM. Multi-lingual handwriting recovery framework based on convolutional denoising autoencoder with attention model. Multimed Tools Appl. 2024;83(8):22295\u2013326.","journal-title":"Multimed Tools Appl"},{"key":"10382_CR25","doi-asserted-by":"publisher","unstructured":"Rabhi B, Elbaati A, Hamdani TM, Alimi AM. ASAR 2021 competition on online signal restoration using Arabic handwriting Dhad dataset. In Document Analysis and Recognition\u2013ICDAR 2021 Workshops: Lausanne, Switzerland, September 5\u201310, Proceedings, Part I 16. Springer International Publishing. 2021;366-378. https:\/\/doi.org\/10.1007\/978-3-030-86198-8_26.","DOI":"10.1007\/978-3-030-86198-8_26"},{"key":"10382_CR26","doi-asserted-by":"crossref","unstructured":"Wu H, Xiao B, Codella N, Liu M, Dai X, Yuan L, Zhang L. Cvt: introducing convolutions to vision transformers. In: Proceedings of the IEEE\/CVF international conference on computer vision. 2021. pp. 22\u201331.","DOI":"10.1109\/ICCV48922.2021.00009"},{"key":"10382_CR27","doi-asserted-by":"publisher","unstructured":"Yahia H, Rabhi B, Dhieb T, Alimi AM. Multi-head self-attention and BGRU for online Arabic grapheme text segmentation. 2023 International Conference on Cyberworlds (CW), Sousse, Tunisia. 2023;78\u201385. https:\/\/doi.org\/10.1109\/CW58918.2023.00021.","DOI":"10.1109\/CW58918.2023.00021"},{"key":"10382_CR28","doi-asserted-by":"publisher","unstructured":"Viard-Gaudin C, Lallican PM, Knerr S, Binter P. The ireste on\/off (ironoff) dual handwriting database. In Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR. 1999;455\u2013458.\u00a0https:\/\/doi.org\/10.1109\/ICDAR.1999.791823.","DOI":"10.1109\/ICDAR.1999.791823"},{"key":"10382_CR29","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1007\/s10032-021-00376-2","volume":"24","author":"Y Hamdi","year":"2021","unstructured":"Hamdi Y, Boubaker H, Alimi AM. Data augmentation using geometric, frequency, and beta modeling approaches for improving multi-lingual online handwriting recognition. IJDAR. 2021;24:283\u201398. https:\/\/doi.org\/10.1007\/s10032-021-00376-2.","journal-title":"IJDAR"},{"key":"10382_CR30","doi-asserted-by":"publisher","unstructured":"Hamdi Y, Boubaker H, Dhieb T, Elbaati A, Alimi AM. Hybrid DBLSTM-SVM based beta-elliptic-CNN models for online Arabic characters recognition. In 2019 International conference on document analysis and recognition (ICDAR).2019;545\u2013550. IEEE.\u00a0https:\/\/doi.org\/10.1109\/ICDAR.2019.00093.","DOI":"10.1109\/ICDAR.2019.00093"},{"key":"10382_CR31","doi-asserted-by":"publisher","unstructured":"Hamdi Y, Boubaker H, Rabhi B, Abdulrahman MQ, Alharithi FS, Almutiry O, Dhahri H, Alimi AM. Deep learned BLSTM for online handwriting modeling simulating the Beta-Elliptic approach. Eng Sci Technol, an International Journal. 2022;35. https:\/\/doi.org\/10.1016\/j.jestch.2022.101215.","DOI":"10.1016\/j.jestch.2022.101215"},{"key":"10382_CR32","doi-asserted-by":"publisher","unstructured":"Lu C, Tang J, Yan S, Lin Z. Generalized nonconvex nonsmooth low-rank minimization. In: Proceedings of the IEEE conference on computer vision and pattern recognition. 2014;4130\u20134137.\u00a0https:\/\/doi.org\/10.1109\/CVPR.2014.526.","DOI":"10.1109\/CVPR.2014.526"},{"issue":"1","key":"10382_CR33","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1007\/s12559-022-10073-9","volume":"15","author":"F Wang","year":"2023","unstructured":"Wang F, Tian S, Yu L, Liu J, Wang J, Li K, Wang Y. TEDT: transformer-based encoding\u2013decoding translation network for multimodal sentiment analysis. Cogn Comput. 2023;15(1):289\u2013303.","journal-title":"Cogn Comput"},{"issue":"2","key":"10382_CR34","doi-asserted-by":"publisher","first-page":"590","DOI":"10.1007\/s12559-022-10066-8","volume":"15","author":"\u00c1 Huertas-Garc\u00eda","year":"2023","unstructured":"Huertas-Garc\u00eda \u00c1, Mart\u00edn A, Huertas-Tato J, Camacho D. Exploring dimensionality reduction techniques in multilingual transformers. Cogn Comput. 2023;15(2):590\u2013612.","journal-title":"Cogn Comput"},{"key":"10382_CR35","doi-asserted-by":"publisher","first-page":"18569","DOI":"10.1109\/ACCESS.2021.3053618","volume":"9","author":"N Rahal","year":"2021","unstructured":"Rahal N, Tounsi M, Hussain A, Alimi AM. Deep sparse auto-encoder features learning for Arabic text recognition. IEEE Access. 2021;9:18569\u201384.","journal-title":"IEEE Access"},{"key":"10382_CR36","doi-asserted-by":"crossref","unstructured":"Dhahri H, Rabhi B, Chelbi S, Almutiry O, Mahmood A, Alimi AM. Automatic detection of COVID-19 using a stacked denoising convolutional autoencoder. Comput, Mater Continua. 2021;69(3):3259.","DOI":"10.32604\/cmc.2021.018449"},{"key":"10382_CR37","doi-asserted-by":"crossref","unstructured":"Rabhi B, Dhahri H, Alimi AM, Alturki FA. Grey wolf optimizer for training Elman neural network. In Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016). 2017;380\u2013390. Springer International Publishing.","DOI":"10.1007\/978-3-319-52941-7_38"},{"key":"10382_CR38","doi-asserted-by":"publisher","first-page":"64963","DOI":"10.1007\/s11042-023-17844-y","volume":"83","author":"K Han","year":"2024","unstructured":"Han K, You W, Deng H, et al. LanT: finding experts for digital calligraphy character restoration. Multimed Tools Appl. 2024;83:64963\u201386. https:\/\/doi.org\/10.1007\/s11042-023-17844-y.","journal-title":"Multimed Tools Appl"}],"container-title":["Cognitive Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-024-10382-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12559-024-10382-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-024-10382-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T07:33:00Z","timestamp":1740814380000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12559-024-10382-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,23]]},"references-count":38,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["10382"],"URL":"https:\/\/doi.org\/10.1007\/s12559-024-10382-1","relation":{},"ISSN":["1866-9956","1866-9964"],"issn-type":[{"value":"1866-9956","type":"print"},{"value":"1866-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,23]]},"assertion":[{"value":"26 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 August 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 November 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Approval"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interest"}}],"article-number":"6"}}