{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:27:21Z","timestamp":1776810441278,"version":"3.51.2"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T00:00:00Z","timestamp":1730937600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T00:00:00Z","timestamp":1730937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Department of Science and Technology, GoI","award":["SEED\/TIDE\/063\/2016"],"award-info":[{"award-number":["SEED\/TIDE\/063\/2016"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Univ Access Inf Soc"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1007\/s10209-024-01162-7","type":"journal-article","created":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T11:02:30Z","timestamp":1730977350000},"page":"1673-1685","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Dynamic gesture recognition using hand pose-based neural networks for sign language interpretation"],"prefix":"10.1007","volume":"24","author":[{"given":"Vaidehi","family":"Sharma","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nehil","family":"Sood","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohita","family":"Jaiswal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abhishek","family":"Sharma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandeep","family":"Saini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jieh-Ren","family":"Chang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,11,7]]},"reference":[{"key":"1162_CR1","doi-asserted-by":"crossref","unstructured":"Rastgoo, R., Kiani, K., Escalera, S.: Video-based isolated hand sign language recognition using a deep cascaded model. Multimed. Tools Appl. 79 (2020)","DOI":"10.1007\/s11042-020-09048-5"},{"key":"1162_CR2","doi-asserted-by":"crossref","unstructured":"Li, D., Opazo, C.R., Yu, X., Li, H.: Word-level deep sign language recognition from video: a new large-scale dataset and methods comparison. In: 2020 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1448\u20131458 (2020)","DOI":"10.1109\/WACV45572.2020.9093512"},{"key":"1162_CR3","doi-asserted-by":"publisher","first-page":"113336","DOI":"10.1016\/j.eswa.2020.113336","volume":"150","author":"R Rastgoo","year":"2020","unstructured":"Rastgoo, R., Kiani, K., Escalera, S.: Hand sign language recognition using multi-view hand skeleton. Expert Syst. Appl. 150, 113336 (2020)","journal-title":"Expert Syst. Appl."},{"key":"1162_CR4","doi-asserted-by":"crossref","unstructured":"Ferreira, P.M., Cardoso, J.S., Rebelo, A.: Multimodal learning for sign language recognition. In: IbPRIA (2017)","DOI":"10.1007\/978-3-319-58838-4_35"},{"key":"1162_CR5","doi-asserted-by":"publisher","first-page":"527","DOI":"10.3390\/rs13030527","volume":"13","author":"KD Kallu","year":"2021","unstructured":"Kallu, K.D., Ahmed, S., Cho, S.H.: Hand gestures recognition using radar sensors for human-computer-interaction: a review. Remote Sens. 13, 527 (2021)","journal-title":"Remote Sens."},{"key":"1162_CR6","doi-asserted-by":"crossref","unstructured":"Selvaraj, P., NC, G., Kumar, P., Khapra, M.: OpenHands: Making sign language recognition accessible with pose-based pretrained models across languages (2021)","DOI":"10.18653\/v1\/2022.acl-long.150"},{"issue":"11","key":"1162_CR7","doi-asserted-by":"publisher","first-page":"1780","DOI":"10.3390\/electronics11111780","volume":"11","author":"D Kothadiya","year":"2022","unstructured":"Kothadiya, D., Bhatt, C., Sapariya, K., Patel, K., Gil-Gonz\u00e1lez, A.-B., Corchado, J.M.: Deepsign: sign language detection and recognition using deep learning. Electronics 11(11), 1780 (2022). https:\/\/doi.org\/10.3390\/electronics11111780","journal-title":"Electronics"},{"key":"1162_CR8","doi-asserted-by":"crossref","unstructured":"K\u00f6p\u00fckl\u00fc, O., K\u00f6se, N., Rigoll, G.: Motion fused frames: data level fusion strategy for hand gesture recognition. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2184\u201321848 (2018)","DOI":"10.1109\/CVPRW.2018.00284"},{"key":"1162_CR9","doi-asserted-by":"crossref","unstructured":"Wang, M., Chen, X., Liu, W., Qian, C., Lin, L., Ma, L.: Drpose3d: depth ranking in 3d human pose estimation. arXiv preprint arXiv:1805.08973 (2018)","DOI":"10.24963\/ijcai.2018\/136"},{"key":"1162_CR10","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1016\/j.jvcir.2018.07.010","volume":"55","author":"MJ Marin-Jimenez","year":"2018","unstructured":"Marin-Jimenez, M.J., Romero-Ramirez, F.J., Munoz-Salinas, R., Medina-Carnicer, R.: 3d human pose estimation from depth maps using a deep combination of poses. J. Vis. Commun. Image Represent. 55, 627\u2013639 (2018)","journal-title":"J. Vis. Commun. Image Represent."},{"key":"1162_CR11","doi-asserted-by":"publisher","first-page":"19917","DOI":"10.1007\/s11042-019-7263-7","volume":"78","author":"K Lim","year":"2019","unstructured":"Lim, K., Tan, A., Lee, C.-P., Tan, S.: Isolated sign language recognition using convolutional neural network hand modelling and hand energy image. Multimed. Tools Appl. 78, 19917\u201319944 (2019). https:\/\/doi.org\/10.1007\/s11042-019-7263-7","journal-title":"Multimed. Tools Appl."},{"key":"1162_CR12","unstructured":"Chen, Y., Zhao, L., Peng, X., Yuan, J., Metaxas, D.N.: Construct dynamic graphs for hand gesture recognition via spatial-temporal attention. arXiv preprint arXiv:1907.08871 (2019)"},{"key":"1162_CR13","doi-asserted-by":"crossref","unstructured":"Zimmermann, C., Brox, T.: Learning to estimate 3d hand pose from single rgb images. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4903\u20134911 (2017)","DOI":"10.1109\/ICCV.2017.525"},{"key":"1162_CR14","doi-asserted-by":"crossref","unstructured":"Gandhi, J., Gandhi, P., Gosar, A., Chaudhari, S.: Video recognition techniques for indian sign language in healthcare domain. In: 2021 2nd International Conference for Emerging Technology (INCET) (2021)","DOI":"10.1109\/INCET51464.2021.9456116"},{"key":"1162_CR15","doi-asserted-by":"publisher","first-page":"107395","DOI":"10.1016\/j.compeleceng.2021.107395","volume":"95","author":"W Abdul","year":"2021","unstructured":"Abdul, W., Alsulaiman, M., Amin, S.U., Faisal, M., Muhammad, G., Albogamy, F.R., Bencherif, M.A., Ghaleb, H.: Intelligent real-time arabic sign language classification using attention-based inception and bilstm. Comput. Electr. Eng. 95, 107395 (2021)","journal-title":"Comput. Electr. Eng."},{"key":"1162_CR16","doi-asserted-by":"publisher","first-page":"59612","DOI":"10.1109\/ACCESS.2021.3069714","volume":"9","author":"MA Bencherif","year":"2021","unstructured":"Bencherif, M.A., Algabri, M., Mekhtiche, M.A., Faisal, M., Alsulaiman, M., Mathkour, H., Al-Hammadi, M., Ghaleb, H.: Arabic sign language recognition system using 2d hands and body skeleton data. IEEE Access 9, 59612\u201359627 (2021)","journal-title":"IEEE Access"},{"key":"1162_CR17","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.4002121","author":"M-H Huang","year":"2022","unstructured":"Huang, M.-H., Wang, H.-M., Sun, C.-T.: A video-based taiwan sign language recognition system using deep learning techniques. SSRN Electron. J. (2022). https:\/\/doi.org\/10.2139\/ssrn.4002121","journal-title":"SSRN Electron. J."},{"key":"1162_CR18","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3165069","author":"J-H Song","year":"2022","unstructured":"Song, J.-H., Kong, K., Kang, S.-J.: Dynamic hand gesture recognition using improved spatio-temporal graph convolutional network. IEEE Trans. Circuits Syst. Video Technol. (2022). https:\/\/doi.org\/10.1109\/TCSVT.2022.3165069","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"1162_CR19","doi-asserted-by":"publisher","first-page":"118914","DOI":"10.1016\/j.eswa.2022.118914","volume":"213","author":"S Das","year":"2023","unstructured":"Das, S., Imtiaz, M.S., Neom, N.H., Siddique, N., Wang, H.: A hybrid approach for bangla sign language recognition using deep transfer learning model with random forest classifier. Expert Syst. Appl. 213, 118914 (2023)","journal-title":"Expert Syst. Appl."},{"issue":"2","key":"1162_CR20","doi-asserted-by":"publisher","first-page":"182","DOI":"10.3390\/electronics10020182","volume":"10","author":"A Dayal","year":"2021","unstructured":"Dayal, A., Paluru, N., Cenkeramaddi, L.R., Yalavarthy, P.K.: Design and implementation of deep learning based contactless authentication system using hand gestures. Electronics 10(2), 182 (2021). https:\/\/doi.org\/10.3390\/electronics10020182","journal-title":"Electronics"},{"issue":"1","key":"1162_CR21","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1007\/s12652-021-02920-8","volume":"13","author":"R Rastgoo","year":"2022","unstructured":"Rastgoo, R., Kiani, K., Escalera, S.: Real-time isolated hand sign language recognition using deep networks and SVD. J. Ambient. Intell. Humaniz. Comput. 13(1), 591\u2013611 (2022)","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"key":"1162_CR22","doi-asserted-by":"crossref","unstructured":"Sharma, V., Jaiswal, M., Sharma, A., Saini, S., Tomar, R.: Dynamic two hand gesture recognition using CNN-LSTM based networks. In: 2021 IEEE International Symposium on Smart Electronic Systems (iSES), pp. 224\u2013229 (2021)","DOI":"10.1109\/iSES52644.2021.00059"},{"key":"1162_CR23","unstructured":"Zhang, F., Bazarevsky, V., Vakunov, A., Tkachenka, A., Sung, G., Chang, C.-L., Grundmann, M.: Mediapipe hands: on-device real-time hand tracking. arXiv preprint arXiv:2006.10214 (2020)"},{"key":"1162_CR24","doi-asserted-by":"publisher","first-page":"60039","DOI":"10.1109\/ACCESS.2022.3179577","volume":"10","author":"S Montaha","year":"2022","unstructured":"Montaha, S., Azam, S., Rafid, A.R.H., Hasan, M.Z., Karim, A., Islam, A.: Timedistributed-CNN-LSTM: a hybrid approach combining CNN and LSTM to classify brain tumor on 3d MRI scans performing ablation study. IEEE Access 10, 60039\u201360059 (2022)","journal-title":"IEEE Access"},{"key":"1162_CR25","unstructured":"Elakkiya, R., Natarajan, B.: Isl-csltr: Indian sign language dataset for continuous sign language translation and recognition. Mendeley Data (2021)"},{"key":"1162_CR26","doi-asserted-by":"publisher","first-page":"22965","DOI":"10.1007\/s11042-020-09048-5","volume":"79","author":"R Rastgoo","year":"2020","unstructured":"Rastgoo, R., Kiani, K., Escalera, S.: Video-based isolated hand sign language recognition using a deep cascaded model. Multimed. Tools Appl. 79, 22965\u201322987 (2020)","journal-title":"Multimed. Tools Appl."},{"issue":"2","key":"1162_CR27","doi-asserted-by":"publisher","first-page":"1349","DOI":"10.1007\/s13369-022-06843-0","volume":"48","author":"A Venugopalan","year":"2023","unstructured":"Venugopalan, A., Reghunadhan, R.: Applying hybrid deep neural network for the recognition of sign language words used by the deaf covid-19 patients. Arab. J. Sci. Eng. 48(2), 1349\u20131362 (2023)","journal-title":"Arab. J. Sci. Eng."},{"key":"1162_CR28","doi-asserted-by":"publisher","first-page":"706","DOI":"10.3390\/s22030706","volume":"22","author":"J Sahoo","year":"2022","unstructured":"Sahoo, J., Prakash, A., P\u0142awiak, P., Samantray, S.: Real-time hand gesture recognition using fine-tuned convolutional neural network. Sensors 22, 706 (2022)","journal-title":"Sensors"},{"key":"1162_CR29","doi-asserted-by":"crossref","unstructured":"Boh\u00e1\u010dek, M., Hr\u00faz, M.: Sign pose-based transformer for word-level sign language recognition. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 182\u2013191 (2022)","DOI":"10.1109\/WACVW54805.2022.00024"},{"issue":"16","key":"1162_CR30","doi-asserted-by":"publisher","first-page":"7156","DOI":"10.3390\/s23167156","volume":"23","author":"KK Podder","year":"2023","unstructured":"Podder, K.K., Ezeddin, M., Chowdhury, M.E., Sumon, M.S.I., Tahir, A.M., Ayari, M.A., Dutta, P., Khandakar, A., Mahbub, Z.B., Kadir, M.A.: Signer-independent arabic sign language recognition system using deep learning model. Sensors 23(16), 7156 (2023)","journal-title":"Sensors"},{"key":"1162_CR31","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/4828102","author":"Y Liu","year":"2021","unstructured":"Liu, Y., Jiang, D., Duan, H., Sun, Y., Li, G., Tao, B., Yun, J., Liu, Y., Chen, B.: Dynamic gesture recognition algorithm based on 3d convolutional neural network. Comput. Intell. Neurosci. (2021). https:\/\/doi.org\/10.1155\/2021\/4828102","journal-title":"Comput. Intell. Neurosci."},{"issue":"9","key":"1162_CR32","doi-asserted-by":"publisher","first-page":"4164","DOI":"10.3390\/app11094164","volume":"11","author":"A Mujahid","year":"2021","unstructured":"Mujahid, A., Awan, M.J., Yasin, A., Mohammed, M.A., Dama\u0161evi\u010dius, R., Maskeli\u016bnas, R., Abdulkareem, K.H.: Real-time hand gesture recognition based on deep learning yolov3 model. Appl. Sci. 11(9), 4164 (2021)","journal-title":"Appl. Sci."},{"issue":"5","key":"1162_CR33","doi-asserted-by":"publisher","first-page":"3029","DOI":"10.3390\/app13053029","volume":"13","author":"J Shin","year":"2023","unstructured":"Shin, J., Musa Miah, A.S., Hasan, M.A.M., Hirooka, K., Suzuki, K., Lee, H.-S., Jang, S.-W.: Korean sign language recognition using transformer-based deep neural network. Appl. Sci. 13(5), 3029 (2023)","journal-title":"Appl. Sci."}],"container-title":["Universal Access in the Information Society"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10209-024-01162-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10209-024-01162-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10209-024-01162-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T09:46:42Z","timestamp":1750153602000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10209-024-01162-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,7]]},"references-count":33,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["1162"],"URL":"https:\/\/doi.org\/10.1007\/s10209-024-01162-7","relation":{},"ISSN":["1615-5289","1615-5297"],"issn-type":[{"value":"1615-5289","type":"print"},{"value":"1615-5297","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,7]]},"assertion":[{"value":"8 October 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 November 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Authors are required to disclose financial or non-financial interests that are directly or indirectly related to the work submitted for publication.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}