{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T06:34:20Z","timestamp":1743057260897,"version":"3.40.3"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030895075"},{"type":"electronic","value":"9783030895082"}],"license":[{"start":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T00:00:00Z","timestamp":1635379200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T00:00:00Z","timestamp":1635379200000},"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\/978-3-030-89508-2_82","type":"book-chapter","created":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T13:04:19Z","timestamp":1635339859000},"page":"639-646","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Handwritten Font Image Design System Based on Deep Learning Algorithm"],"prefix":"10.1007","author":[{"given":"Yan","family":"Lin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,28]]},"reference":[{"issue":"9","key":"82_CR1","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","volume":"42","author":"G Litjens","year":"2017","unstructured":"Litjens, G., Kooi, T., Bejnordi, B.E., et al.: A survey on deep learning in medical image analysis. Med. Image Anal. 42(9), 60\u201388 (2017)","journal-title":"Med. Image Anal."},{"key":"82_CR2","doi-asserted-by":"crossref","unstructured":"Sheng, W., Sun, S., Zhen, L., et al.: Accurate de novo prediction of protein contact map by ultra-deep learning model. Plos Comput. Biol. 13(1), e1005324 (2017)","DOI":"10.1371\/journal.pcbi.1005324"},{"issue":"5","key":"82_CR3","doi-asserted-by":"publisher","first-page":"1122","DOI":"10.1016\/j.cell.2018.02.010","volume":"172","author":"DS Kermany","year":"2018","unstructured":"Kermany, D.S., Goldbaum, M., Ca, I.W., et al.: Identifying medical diagnoses and treatable diseases by image-based deep learning. Cell 172(5), 1122-1131.e9 (2018)","journal-title":"Cell"},{"key":"82_CR4","unstructured":"Lee, J.: Integration of digital twin and deep learning in cyber-physical systems: towards Smart Manuf. 38(8), 901\u2013910 (2020)"},{"issue":"1","key":"82_CR5","first-page":"763","volume":"66","author":"X Wang","year":"2016","unstructured":"Wang, X., Gao, L., Mao, S., et al.: CSI-based fingerprinting for indoor localization: a deep learning approach. IEEE Trans. Veh. Technol. 66(1), 763\u2013776 (2016)","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"12","key":"82_CR6","doi-asserted-by":"publisher","first-page":"2825","DOI":"10.1109\/TCYB.2015.2490165","volume":"46","author":"Y Chherawala","year":"2016","unstructured":"Chherawala, Y., Roy, P.P., Cheriet, M.: Feature set evaluation for offline handwriting recognition systems: application to the recurrent neural network model. IEEE Trans. Cybernet. 46(12), 2825\u20132836 (2016)","journal-title":"IEEE Trans. Cybernet."},{"key":"82_CR7","unstructured":"Impedovo, D., Pirlo, G.: Dynamic handwriting analysis for the assessment of neurodegenerative diseases: a pattern recognition perspective. IEEE Rev. Biomed. Eng. 99, 1\u20131 (2018)"},{"issue":"3","key":"82_CR8","doi-asserted-by":"publisher","first-page":"122","DOI":"10.5539\/jel.v5n3p122","volume":"5","author":"N Khatun","year":"2016","unstructured":"Khatun, N., Miwa, J.: An autonomous learning system of bengali characters using web-based intelligent handwriting recognition. J. Educ. Learn. 5(3), 122 (2016)","journal-title":"J. Educ. Learn."},{"issue":"7","key":"82_CR9","doi-asserted-by":"publisher","first-page":"2093","DOI":"10.1007\/s10489-020-01632-4","volume":"50","author":"S Singh","year":"2020","unstructured":"Singh, S., Chauhan, V.K., Smith, E.H.B.: A self controlled RDP approach for feature extraction in online handwriting recognition using deep learning. Appl. Intell. 50(7), 2093\u20132104 (2020). https:\/\/doi.org\/10.1007\/s10489-020-01632-4","journal-title":"Appl. Intell."},{"issue":"1","key":"82_CR10","doi-asserted-by":"publisher","first-page":"2250015","DOI":"10.1142\/S0219467822500152","volume":"21","author":"M Gagaoua","year":"2021","unstructured":"Gagaoua, M., Ghilas, H., Tari, A., et al.: Histogram of marked background (HMB) feature extraction method for Arabic handwriting recognition. Int. J. Image Graph. 21(1), 2250015 (2021)","journal-title":"Int. J. Image Graph."},{"issue":"2","key":"82_CR11","doi-asserted-by":"publisher","first-page":"101","DOI":"10.3233\/AIC-170562","volume":"32","author":"J Pastor-Pellicer","year":"2019","unstructured":"Pastor-Pellicer, J., Castro-Bleda, M.J., Espana-Boquera, S., et al.: Handwriting recognition by using deep learning to extract meaningful features. AI Commun. 32(2), 101\u2013112 (2019)","journal-title":"AI Commun."},{"key":"82_CR12","doi-asserted-by":"crossref","unstructured":"Likforman-Sulem, L., Sposito, A.E., Faundez-Zanuy, M., et al.: EMOTHAW: a novel database for emotional state recognition from handwriting and drawing. IEEE Trans. Hum.-Mach. Syst. 47(2), 273\u2013284 (2016)","DOI":"10.1109\/THMS.2016.2635441"}],"container-title":["Lecture Notes on Data Engineering and Communications Technologies","The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-89508-2_82","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T13:12:33Z","timestamp":1635340353000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-89508-2_82"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,28]]},"ISBN":["9783030895075","9783030895082"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-89508-2_82","relation":{},"ISSN":["2367-4512","2367-4520"],"issn-type":[{"type":"print","value":"2367-4512"},{"type":"electronic","value":"2367-4520"}],"subject":[],"published":{"date-parts":[[2021,10,28]]},"assertion":[{"value":"28 October 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SPIoT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 November 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 November 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"spiot2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.spiot.net.cn\/SPIOT2021","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}