{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T16:59:36Z","timestamp":1742921976054,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031821523"},{"type":"electronic","value":"9783031821530"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-82153-0_1","type":"book-chapter","created":{"date-parts":[[2025,3,4]],"date-time":"2025-03-04T07:05:16Z","timestamp":1741071916000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning Approach for\u00a0Tunisian Postal Address Segmentation"],"prefix":"10.1007","author":[{"given":"Fadoua","family":"Bouafif","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Linda","family":"Abdellatif","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,3,5]]},"reference":[{"key":"1_CR1","unstructured":"Mekala V., Manimegalai M., Sasipriya K., Selvakani K., Sriram Gautham J.: Digital Address Identification From Handwritten Address. Postcards. Int. J. Sci. Technol. Res. 9(02) (2020)"},{"key":"1_CR2","doi-asserted-by":"crossref","unstructured":"Albahli S., Javed A., Nawaz M., Irtaza A.:An improved faster RCNN model for handwritten character recognition. Arab. J. Sci. Eng. (2021)","DOI":"10.1007\/s13369-021-05471-4"},{"key":"1_CR3","doi-asserted-by":"crossref","unstructured":"Charfi M., Kherallah M., El Baati A. , Alimi A. M.:A new approach for arabic handwritten postal addresses recognition. Int. J. Adv. Comput. Sci. Appl. 3(3) (2012)","DOI":"10.14569\/IJACSA.2012.030301"},{"key":"1_CR4","doi-asserted-by":"crossref","unstructured":"Shi, B., Bai, X., Yao, C.: An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition. IEEE Trans. Pattern Anal. Mach. Intell. 39(11), 2298\u20132304 (2017)","DOI":"10.1109\/TPAMI.2016.2646371"},{"key":"1_CR5","doi-asserted-by":"publisher","unstructured":"Ali, S., Shaukat, Z., Azeem, M., Sakhawat, Z., Mahmood, T., ur Rehman, K.: An efficient and improved scheme for handwritten digit recognition based on convolutional neural network. SN Appl. Sci. 1(9) (2019). https:\/\/doi.org\/10.1007\/s42452-019-1161-5","DOI":"10.1007\/s42452-019-1161-5"},{"key":"1_CR6","unstructured":"Hafiz, A.M. Bhat, G.M.: Reinforcement learning based handwritten digit recognition with two-state Q-learning. Comput. Vision Pattern Recogn. 1 (2020)"},{"key":"1_CR7","doi-asserted-by":"publisher","unstructured":"Ahlawat, S., Choudhary, A., Nayyar, A., Singh, S., Yoon, B.: Improved handwritten digit recognition using convolutional neural networks (CNN). Sensors 20(12), 3344 (2020). https:\/\/doi.org\/10.3390\/s20123344","DOI":"10.3390\/s20123344"},{"key":"1_CR8","doi-asserted-by":"publisher","unstructured":"Alzubaidi, L., et al.: Review of deep learning: concepts, CNN architectures, challenges, applications, future directions. J. Big Data 8(1) (2021). https:\/\/doi.org\/10.1186\/s40537-021-00444-8","DOI":"10.1186\/s40537-021-00444-8"},{"key":"1_CR9","doi-asserted-by":"crossref","unstructured":"Al-Taani, A.T., Ahmad, S.T.: Recognition of arabic handwritten characters using residual neural networks. Jordanian J. Comput. Inform. Technol. (JJCIT) 07(02) (2021)","DOI":"10.5455\/jjcit.71-1615204606"},{"key":"1_CR10","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). https:\/\/doi.org\/10.1016\/j.procs.2016.05.512","journal-title":"Procedia Comput. Sci."},{"key":"1_CR11","doi-asserted-by":"publisher","first-page":"556","DOI":"10.1016\/j.procs.2015.09.130","volume":"65","author":"JH AlKhateeb","year":"2015","unstructured":"AlKhateeb, J.H.: A database for Arabic handwritten character recognition. Proc. Comput. Sci. 65, 556\u2013561 (2015)","journal-title":"Proc. Comput. Sci."},{"key":"1_CR12","doi-asserted-by":"publisher","unstructured":"Khateeb, Y.: Arabic hand-written character recognition based on deep convolutional neural networks. Jordanian J. Comput. Inform. Technol. 3(3), 186 (2017). https:\/\/doi.org\/10.5455\/jjcit.71-1498142206","DOI":"10.5455\/jjcit.71-1498142206"},{"key":"1_CR13","doi-asserted-by":"crossref","unstructured":"Al-Taani, A.T., Ahmad, S.T.:recognition of Arabic handwritten characters using residual neural networKS. Jordanian J. Comput. Inform. Technol. (JJCIT) 07, 02 (2021)","DOI":"10.5455\/jjcit.71-1615204606"},{"key":"1_CR14","doi-asserted-by":"crossref","unstructured":"AL-Taee, M.M., Neji, S.B.H., Frikha, M., Allawi, S.T.: Classification and Localization of Arabic Handwritten Text in KHATT Dataset Based on Faster R-CNN. Power Syst. Technol. 47(4), 426\u2013447(2024)","DOI":"10.52783\/pst.213"},{"key":"1_CR15","doi-asserted-by":"crossref","unstructured":"Al-wajih, E., Ghazali, R. and Hassim, Y.M.M.: Residual neural network vs local binary convolutional neural networks for bilingual handwritten digit recognition. In: International Conference on Soft Computing and Data Mining, pp. 25\u201334 (2020)","DOI":"10.1007\/978-3-030-36056-6_3"},{"key":"1_CR16","doi-asserted-by":"crossref","unstructured":"Hou, Y., Zhao, H.: Handwritten digit recognition based on depth neural network. In: International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS), pp. 35\u201338 (2017)","DOI":"10.1109\/ICIIBMS.2017.8279710"},{"key":"1_CR17","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.neunet.2018.02.010","volume":"107","author":"J Qiao","year":"2018","unstructured":"Qiao, J., Wang, G., Li, W., Chen, M.: An adaptive deep Q-learning strategy for handwritten digit recognition. Neural Netw. 107, 61\u201371 (2018). https:\/\/doi.org\/10.1016\/j.neunet.2018.02.010","journal-title":"Neural Netw."},{"key":"1_CR18","unstructured":"Ghoury, S., Sungur, C., Durdu, A.: Real-time diseases detection of grape and grape leaves using faster r-cnn and ssd mobilenet architectures. In: International Conference on Advanced Technologies, Computer Engineering and Science ICATCES (2019)"},{"key":"1_CR19","unstructured":"Ren, S., He, K., Girshick, Sun, J.R.: Faster r-cnn: towards real-time object detection with region proposal networks. In: Advances in Neural Information Processing Systems, pp. 91\u201399 (2016)"},{"key":"1_CR20","doi-asserted-by":"crossref","unstructured":"Gattal A., Chibani, Y.: Segmentation Strategy of Handwritten Connected Digits (SSHCD). In: Image Analysis and Processing, pp. 248\u2013254 (2011)","DOI":"10.1007\/978-3-642-24088-1_26"}],"container-title":["Communications in Computer and Information Science","Intelligent Systems and Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-82153-0_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,4]],"date-time":"2025-03-04T07:05:33Z","timestamp":1741071933000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-82153-0_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031821523","9783031821530"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-82153-0_1","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"5 March 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Systems and Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Istanbul","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"T\u00fcrkiye","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ispr22024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ispr2024.sciencesconf.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}