{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T00:54:14Z","timestamp":1775609654540,"version":"3.50.1"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031581809","type":"print"},{"value":"9783031581816","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-58181-6_29","type":"book-chapter","created":{"date-parts":[[2024,7,2]],"date-time":"2024-07-02T10:03:42Z","timestamp":1719914622000},"page":"343-356","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Isolated Sign Language Recognition Using Deep Learning"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-3451-2688","authenticated-orcid":false,"given":"Sukanya","family":"Das","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8699-9840","authenticated-orcid":false,"given":"Sumit Kumar","family":"Yadav","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6104-3771","authenticated-orcid":false,"given":"Debasis","family":"Samanta","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,3]]},"reference":[{"key":"29_CR1","doi-asserted-by":"publisher","first-page":"79491","DOI":"10.1109\/ACCESS.2020.2990434","volume":"8","author":"M Al-Hammadi","year":"2020","unstructured":"Al-Hammadi, M., Muhammad, G., Abdul, W., Alsulaiman, M., Bencherif, M.A., Mekhtiche, M.A.: Hand gesture recognition for sign language using 3DCNN. IEEE Access 8, 79491\u201379509 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.2990434","journal-title":"IEEE Access"},{"key":"29_CR2","doi-asserted-by":"publisher","first-page":"126917","DOI":"10.1109\/ACCESS.2021.3110912","volume":"9","author":"M Al-Qurishi","year":"2021","unstructured":"Al-Qurishi, M., Khalid, T., Souissi, R.: Deep learning for sign language recognition: current techniques, benchmarks, and open issues. IEEE Access 9, 126917\u2013126951 (2021). https:\/\/doi.org\/10.1109\/ACCESS.2021.3110912","journal-title":"IEEE Access"},{"key":"29_CR3","doi-asserted-by":"publisher","first-page":"83199","DOI":"10.1109\/ACCESS.2020.2990699","volume":"8","author":"SKH Aly","year":"2020","unstructured":"Aly, S.K.H., Aly, W.: DeepArSLR: a novel signer-independent deep learning framework for isolated Arabic sign language gestures recognition. IEEE Access 8, 83199\u201383212 (2020)","journal-title":"IEEE Access"},{"issue":"1","key":"29_CR4","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1109\/TII.2020.3041618","volume":"18","author":"FS Botros","year":"2020","unstructured":"Botros, F.S., Phinyomark, A., Scheme, E.J.: Electromyography-based gesture recognition: is it time to change focus from the forearm to the wrist? IEEE Trans. Industr. Inf. 18(1), 174\u2013184 (2020)","journal-title":"IEEE Trans. Industr. Inf."},{"key":"29_CR5","doi-asserted-by":"crossref","unstructured":"Dawod, A.Y., Chakpitak, N.: Novel technique for isolated sign language based on fingerspelling recognition. In: 2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), pp.\u00a01\u20138. IEEE (2019)","DOI":"10.1109\/SKIMA47702.2019.8982452"},{"key":"29_CR6","doi-asserted-by":"crossref","unstructured":"Fatmi, R., Rashad, S., Integlia, R.: Comparing ANN, SVM, and HMM based machine learning methods for American sign language recognition using wearable motion sensors. In: 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC), pp. 0290\u20130297. IEEE (2019)","DOI":"10.1109\/CCWC.2019.8666491"},{"key":"29_CR7","doi-asserted-by":"publisher","first-page":"106898","DOI":"10.1016\/j.compeleceng.2020.106898","volume":"90","author":"R Gupta","year":"2021","unstructured":"Gupta, R., Kumar, A.: Indian sign language recognition using wearable sensors and multi-label classification. Comput. Electr. Eng. 90, 106898 (2021)","journal-title":"Comput. Electr. Eng."},{"key":"29_CR8","doi-asserted-by":"publisher","first-page":"105676","DOI":"10.1016\/j.dib.2020.105676","volume":"30","author":"VT Hoang","year":"2020","unstructured":"Hoang, V.T.: HGM-4: a new multi-cameras dataset for hand gesture recognition. Data Brief 30, 105676 (2020)","journal-title":"Data Brief"},{"issue":"8","key":"29_CR9","doi-asserted-by":"publisher","first-page":"3376","DOI":"10.1109\/TII.2017.2779814","volume":"14","author":"S Jiang","year":"2017","unstructured":"Jiang, S., et al.: Feasibility of wrist-worn, real-time hand, and surface gesture recognition via sEMG and IMU sensing. IEEE Trans. Industr. Inf. 14(8), 3376\u20133385 (2017)","journal-title":"IEEE Trans. Industr. Inf."},{"key":"29_CR10","doi-asserted-by":"publisher","unstructured":"Lee, C., Ng, K.K., Chen, C.H., Lau, H., Chung, S., Tsoi, T.: American sign language recognition and training method with recurrent neural network. Expert Syst. Appl. 167, 114403 (2021). https:\/\/doi.org\/10.1016\/j.eswa.2020.114403, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0957417420310745","DOI":"10.1016\/j.eswa.2020.114403"},{"key":"29_CR11","doi-asserted-by":"crossref","unstructured":"Li, D., Rodriguez, C., Yu, X., Li, H.: Word-level deep sign language recognition from video: a new large-scale dataset and methods comparison. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 1459\u20131469 (2020)","DOI":"10.1109\/WACV45572.2020.9093512"},{"key":"29_CR12","doi-asserted-by":"crossref","unstructured":"Mummadi, C.K., et al.: Real-time and embedded detection of hand gestures with an imu-based glove. In: Informatics, vol.\u00a05, p.\u00a028. MDPI (2018)","DOI":"10.3390\/informatics5020028"},{"key":"29_CR13","doi-asserted-by":"publisher","unstructured":"Rastgoo, R., Kiani, K., Escalera, S.: Hand sign language recognition using multi-view hand skeleton. Expert Syst. Appl. 150, 113336 (2020). https:\/\/doi.org\/10.1016\/j.eswa.2020.113336, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0957417420301615","DOI":"10.1016\/j.eswa.2020.113336"},{"key":"29_CR14","doi-asserted-by":"publisher","first-page":"181340","DOI":"10.1109\/access.2020.3028072","volume":"8","author":"OM Sincan","year":"2020","unstructured":"Sincan, O.M., Keles, H.Y.: AUTSL: a large scale multi-modal Turkish sign language dataset and baseline methods. IEEE Access 8, 181340\u2013181355 (2020). https:\/\/doi.org\/10.1109\/access.2020.3028072","journal-title":"IEEE Access"},{"key":"29_CR15","doi-asserted-by":"publisher","unstructured":"V., A., R., R.: A deep convolutional neural network approach for static hand gesture recognition. Procedia Comput. Sci. 171, 2353\u20132361 (2020). https:\/\/doi.org\/10.1016\/j.procs.2020.04.255, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1877050920312473. third International Conference on Computing and Network Communications (CoCoNet\u201919)","DOI":"10.1016\/j.procs.2020.04.255"},{"key":"29_CR16","doi-asserted-by":"publisher","unstructured":"Wei, S., Chen, X., Yang, X., Cao, S., Zhang, X.: A component-based vocabulary-extensible sign language gesture recognition framework. Sensors 16(4) (2016). https:\/\/doi.org\/10.3390\/s16040556, https:\/\/www.mdpi.com\/1424-8220\/16\/4\/556","DOI":"10.3390\/s16040556"},{"key":"29_CR17","first-page":"539","volume":"21","author":"G Yuan","year":"2021","unstructured":"Yuan, G., Liu, X., Yan, Q., Qiao, S., Wang, Z., Yuan, L.: Hand gesture recognition using deep feature fusion network based on wearable sensors. IEEE Sens. J. 21, 539\u2013547 (2021)","journal-title":"IEEE Sens. J."}],"container-title":["Communications in Computer and Information Science","Computer Vision and Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-58181-6_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,2]],"date-time":"2024-07-02T10:09:32Z","timestamp":1719914972000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-58181-6_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031581809","9783031581816"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-58181-6_29","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"3 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CVIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Vision and Image Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jammu","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 November 2023","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":"cvip2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iitjammu.ac.in\/cvip2023\/","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":"Online CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"461","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":"140","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":"30% - 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":"3","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}