{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:52:08Z","timestamp":1758271928573,"version":"3.41.0"},"publisher-location":"Cham","reference-count":42,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319942100"},{"type":"electronic","value":"9783319942117"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"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":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-94211-7_29","type":"book-chapter","created":{"date-parts":[[2018,6,29]],"date-time":"2018-06-29T07:29:59Z","timestamp":1530257399000},"page":"265-274","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Convolutional Feature Learning and CNN Based HMM for Arabic Handwriting Recognition"],"prefix":"10.1007","author":[{"given":"Mustapha","family":"Amrouch","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mouhcine","family":"Rabi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Youssef","family":"Es-Saady","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,6,30]]},"reference":[{"key":"29_CR1","unstructured":"Goodfellow, I.J., Bulatov, Y., Ibarz, J., Arnoud, S., Shet, V.: Multi-digit number recognition from street view imagery using deep convolutional neural networks. In: ICLR (2014)"},{"key":"29_CR2","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems 25 (NIPS 2012)"},{"issue":"3","key":"29_CR3","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, S., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.C., Li, F.F.: Imagenet large scale visual recognition challenge. Int. J. Comput. Vis. 115(3), 211\u2013252 (2015)","journal-title":"Int. J. Comput. Vis."},{"key":"29_CR4","doi-asserted-by":"crossref","unstructured":"Hamdani, M., Doetsch, P., Kozielski, M., El-Desoky Mousaand, A., Ney, H.: The RWTH large vocabulary arabic handwriting recognition system. In: 11th IAPR International Workshop on Document Analysis Systems, pp. 111\u2013115 (2014)","DOI":"10.1109\/DAS.2014.61"},{"key":"29_CR5","series-title":"Studies in Computational Intelligence","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-24797-2","volume-title":"Supervised Sequence Labeling with Recurrent Neural Networks","author":"A Graves","year":"2012","unstructured":"Graves, A.: Supervised Sequence Labeling with Recurrent Neural Networks. Studies in Computational Intelligence. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-24797-2"},{"issue":"4","key":"29_CR6","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1007\/s10032-009-0098-4","volume":"12","author":"T Plotz","year":"2009","unstructured":"Plotz, T., Fink, G.A.: Markov models for offline handwriting recognition: a survey. Int. J. Doc. Anal. Recogn. 12(4), 269\u2013298 (2009)","journal-title":"Int. J. Doc. Anal. Recogn."},{"issue":"4","key":"29_CR7","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1109\/TPAMI.2010.141","volume":"33","author":"S Espana-Boquera","year":"2011","unstructured":"Espana-Boquera, S., Castro-Bleda, M.J., Gorbe-Moya, J., Zamora-Mart\u0131nez, F.: Improving offline handwritten text recognition with Hybrid HMM\/ANN models. IEEE Trans. Pattern Anal. Mach. Intell. 33(4), 767\u2013779 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"29_CR8","doi-asserted-by":"publisher","first-page":"1712","DOI":"10.1016\/j.procs.2016.05.512","volume":"80","author":"M Elleuch","year":"2016","unstructured":"Elleuch, M., Maalej, R., Kherallah, M.: A new design based-SVM of the CNN classifier architecture with dropout for offline arabic handwritten recognition. Procedia Comput. Sci. 80, 1712\u20131723 (2016). Online publication date 1 Jan 2016","journal-title":"Procedia Comput. Sci."},{"key":"29_CR9","doi-asserted-by":"crossref","unstructured":"Ciresan, D.C., Meier, U., Gambardella, L.M., Schmidhuber, J.: Deep big simple neural nets excel on handwritten digit recognition CoRR abs\/1003.0358 (2010)","DOI":"10.1162\/NECO_a_00052"},{"key":"29_CR10","doi-asserted-by":"crossref","unstructured":"Kozielski, M., Doetsch, P., Ney, H.: Improvements in RWTH\u2019s system for off-line handwriting recognition. In: International Conference on Document Analysis and Recognition (ICDAR2013), pp. 935\u2013939 (2013)","DOI":"10.1109\/ICDAR.2013.190"},{"issue":"3","key":"29_CR11","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1109\/TPAMI.2006.55","volume":"28","author":"H Xue","year":"2006","unstructured":"Xue, H., Govindaraju, V.: Hidden Markov models combining discrete symbols and continuous attributes in handwriting recognition. IEEE Trans. Pattern Anal. Mach. Intell. 28(3), 458\u2013462 (2006)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"29_CR12","doi-asserted-by":"crossref","unstructured":"Ahmad, I., Fink, G., Mahmoud, S., et al.: Improvements in sub-character hmm model based arabic text recognition. In: 2014 14th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp. 537\u2013542. IEEE (2014)","DOI":"10.1109\/ICFHR.2014.96"},{"issue":"6","key":"29_CR13","first-page":"1","volume":"4","author":"J Alabodi","year":"2013","unstructured":"Alabodi, J., Li, X.: An effective approach to offline Arabic handwriting recognition. Int. J. Artif. Intell. Appl. 4(6), 1 (2013)","journal-title":"Int. J. Artif. Intell. Appl."},{"issue":"4","key":"29_CR14","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1007\/s10032-013-0201-8","volume":"16","author":"SA Azeem","year":"2013","unstructured":"Azeem, S.A., Ahmed, H.: Effective technique for the recognition of offline arabic handwritten words using hidden markov models. Int. J. Docum. Anal. Recogn. (IJDAR) 16(4), 399\u2013412 (2013)","journal-title":"Int. J. Docum. Anal. Recogn. (IJDAR)"},{"issue":"1","key":"29_CR15","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s10032-010-0117-5","volume":"14","author":"H El Abed","year":"2011","unstructured":"El Abed, H., Margner, V.: ICDAR 2009-Arabic handwriting recognition competition. Int. J. Docum. Anal. Recogn. (IJDAR) 14(1), 3\u201313 (2011)","journal-title":"Int. J. Docum. Anal. Recogn. (IJDAR)"},{"key":"29_CR16","unstructured":"Pechwitz, M., Maddouri, S.S., M\u00e4rgner, V., Ellouze, N., Amiri, H.: IFN\/ENIT-database of handwritten Arabic words. In: The 7th CIFED 2002, Hammamet, Tunis, 21\u201323 October 2002 (2002)"},{"issue":"5","key":"29_CR17","doi-asserted-by":"publisher","first-page":"413","DOI":"10.14257\/ijhit.2014.7.5.38","volume":"7","author":"A Lawgali","year":"2014","unstructured":"Lawgali, A., Angelova, M., Bouridane, A.: A framework for arabic handwritten recognition based on segmentation. Int. J. Hybrid Inf. Technol. 7(5), 413\u2013428 (2014)","journal-title":"Int. J. Hybrid Inf. Technol."},{"issue":"2","key":"29_CR18","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. 45(2), 23\u201335 (2013)","journal-title":"ACM Comput. Surv."},{"key":"29_CR19","doi-asserted-by":"publisher","unstructured":"Rabi, M., Amrouch, M., Mahani, Z., Mammass, D.: Recognition of cursive Arabic handwritten text using embedded training based on HMMs. In: International Conference on Engineering & MIS (ICEMIS), September 2016, INSPEC Accession Number: 16467172. IEEE. https:\/\/doi.org\/10.1109\/icemis.2016.7745330","DOI":"10.1109\/icemis.2016.7745330"},{"key":"29_CR20","doi-asserted-by":"crossref","unstructured":"Bluche, T., Ney, H., Kermorvant, C.: Tandem HMM with convolutional neural network for handwritten word recognition. In: 38th International Conference on Acoustics Speech and Signal Processing (ICASSP2013), pp. 2390\u20132394 (2013)","DOI":"10.1109\/ICASSP.2013.6638083"},{"key":"29_CR21","doi-asserted-by":"crossref","unstructured":"Bluche, T., Ney, H., Kermorvant, C.: Feature extraction with convolutional neural networks for handwritten word recognition. In: 12th International Conference on Document Analysis and Recognition (ICDAR2013) (2013)","DOI":"10.1109\/ICDAR.2013.64"},{"key":"29_CR22","doi-asserted-by":"crossref","unstructured":"Le Cun, Y., Kavukcuoglu, K., Farabet, C.: Convolutional networks and applications in vision. In: International Symposium on Circuits and Systems, pp. 253\u2013256, May 2010","DOI":"10.1109\/ISCAS.2010.5537907"},{"key":"29_CR23","doi-asserted-by":"crossref","unstructured":"Mohamad, R.A.-H., Likforman-Sulem, L., Mokbel, C.: Combining slanted-frame classifiers for improved HMM-based Arabic handwriting recognition. In: IEEE PAMI, vol. 31, no. 7, pp. 1165\u20131177 (2009)","DOI":"10.1109\/TPAMI.2008.136"},{"issue":"3","key":"29_CR24","first-page":"1139","volume":"28","author":"I Sutskever","year":"2013","unstructured":"Sutskever, I., Martens, J., Dahl, G., Hinton, G.: On the importance of initialization and momentum in deep learning. JMLR W&CP 28(3), 1139\u20131147 (2013)","journal-title":"JMLR W&CP"},{"key":"29_CR25","unstructured":"Sermanet, P., Eigen, D., Zhang, X., Mathieu, M., Fergus, R., Le-Cun, Y.: OverFeat: integrated recognition, localization and detection using convolutional network. CoRR (2013)"},{"key":"29_CR26","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich, A.: Going deeper with convolutions. CoRR abs\/1409.4842 (2014)","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"29_CR27","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv technical report (2014)"},{"key":"29_CR28","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition (2015). https:\/\/arxiv.org\/abs\/1512.03385","DOI":"10.1109\/CVPR.2016.90"},{"key":"29_CR29","unstructured":"Nair, V., Hinton, G.E.: Rectified linear units improve restricted boltzmann machines. In: Proceedings of the 27th International Conference on Machine Learning (ICML 2010), pp. 807\u2013814 (2010)"},{"key":"29_CR30","unstructured":"Le Cun, Y., Bottou, L., Bengio, Y.: Reading checks with multilayer graph transformer networks. In: International Conference on Acoustics, Speech, and Signal Processing (1997)"},{"key":"29_CR31","unstructured":"Bengio, Y., Boulanger-Lewandowski, N., Pascanu, R.: Advances in optimizing recurrent networks. CoRR abs\/1212.0901 (2012). http:\/\/arxiv.org\/abs\/1212.0901"},{"issue":"1","key":"29_CR32","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1214\/aoms\/1177697196","volume":"41","author":"LE Baum","year":"1970","unstructured":"Baum, L.E., Petrie, T., Soules, G., Weiss, N.: A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains. Ann. Math. Stat. 41(1), 164\u2013171 (1970). https:\/\/doi.org\/10.1214\/aoms\/1177697196","journal-title":"Ann. Math. Stat."},{"issue":"3","key":"29_CR33","doi-asserted-by":"publisher","first-page":"268","DOI":"10.1109\/proc.1973.9030","volume":"61","author":"GD Forney Jr","year":"1973","unstructured":"Forney Jr., G.D.: The Viterbi algorithm. Proc. IEEE 61(3), 268\u2013278 (1973). https:\/\/doi.org\/10.1109\/proc.1973.9030","journal-title":"Proc. IEEE"},{"key":"29_CR34","unstructured":"Keras (2016). https:\/\/github.com\/fchollet\/keras"},{"key":"29_CR35","volume-title":"The HTK Book V3.4","author":"S Young","year":"2006","unstructured":"Young, S., et al.: The HTK Book V3.4. Cambridge University Press, Cambridge (2006)"},{"key":"29_CR36","doi-asserted-by":"publisher","first-page":"1081","DOI":"10.1016\/j.patrec.2011.02.006","volume":"32","author":"JH Alkhateeb","year":"2011","unstructured":"Alkhateeb, J.H., Ren, J., Jiang, J., Al-Muhtaseb, H.: Offline handwritten Arabic cursive text recognition using hidden markov models and re-ranking. Pattern Recogn. Lett. 32, 1081\u20131088 (2011)","journal-title":"Pattern Recogn. Lett."},{"key":"29_CR37","doi-asserted-by":"crossref","unstructured":"Maqqor, A. Halli, A., Satori, K., Tairi, H.: Off-line recognition handwriting combination of mutiple classifiers, In: 3rd International IEEE Colloquium on Information Science and Technology, IEEE CIST 2014, October 2014","DOI":"10.1109\/CIST.2014.7016629"},{"key":"29_CR38","unstructured":"El Moubtahij, H., Akram, H., Satori, K.: Using features of local densities, statistics and HMM toolkit (HTK) for offline Arabic handwriting text recognition (2016)"},{"key":"29_CR39","unstructured":"Jayech, K., Mahjoub, M.A., Amara, N.E.: Arabic handwritten word recognition based on dynamic bayesian network (2016)"},{"key":"29_CR40","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1016\/j.patrec.2012.09.002","volume":"35","author":"A Gim\u00e9nez","year":"2012","unstructured":"Gim\u00e9nez, A., Khoury, I., Andr\u00e9s-Ferrer, J., Juan, A.: Handwriting word recognition using windowed bernoulli HMMs. Pattern Recogn. Lett 35, 149\u2013156 (2012). Article in Press","journal-title":"Pattern Recogn. Lett"},{"key":"29_CR41","doi-asserted-by":"crossref","unstructured":"Hamdani, M., El Abed, H., Kherallah, M., Alimi, A.: Combining multiple HMMs using online and off-line features for off-line Arabic handwriting recognition. In: Proceedings of the 10th International Conference on Document Analysis and Recognition, pp. 201\u2013205 (2009)","DOI":"10.1109\/ICDAR.2009.40"},{"key":"29_CR42","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.patrec.2009.08.009","volume":"31","author":"Y Kessentini","year":"2010","unstructured":"Kessentini, Y., Paquet, T., Ben Hamadou, A.: Off-line handwritten word recognition using multistream hidden Markov models. Pattern Recogn. Lett. 31, 60\u201370 (2010)","journal-title":"Pattern Recogn. Lett."}],"container-title":["Lecture Notes in Computer Science","Image and Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-94211-7_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T12:19:43Z","timestamp":1751717983000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-94211-7_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319942100","9783319942117"],"references-count":42,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-94211-7_29","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"30 June 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICISP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image and Signal Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cherbourg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 July 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 July 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icisp2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.icisp-conf.org\/index.php.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-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":"122","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":"58","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":"0","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":"48% - 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":"2.2","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":"1.88","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}