{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T22:15:13Z","timestamp":1786400113786,"version":"build-2736575974"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2022,10,29]],"date-time":"2022-10-29T00:00:00Z","timestamp":1667001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,10,29]],"date-time":"2022-10-29T00:00:00Z","timestamp":1667001600000},"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":["Multimed Tools Appl"],"published-print":{"date-parts":[[2023,5]]},"DOI":"10.1007\/s11042-022-14084-4","type":"journal-article","created":{"date-parts":[[2022,10,29]],"date-time":"2022-10-29T09:05:04Z","timestamp":1667034304000},"page":"16905-16927","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["Automated Indian sign language recognition system by fusing deep and handcrafted feature"],"prefix":"10.1007","volume":"82","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3756-186X","authenticated-orcid":false,"given":"Soumen","family":"Das","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saroj Kr","family":"Biswas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Biswajit","family":"Purkayastha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,10,29]]},"reference":[{"key":"14084_CR1","unstructured":"Adithya V, Reghunadhan R (2021) \"Applying deep neural networks for the automatic recognition of sign language words: A communication aid to deaf agriculturists.\" Expert Syst Appl, pp-1-12"},{"key":"14084_CR2","doi-asserted-by":"publisher","unstructured":"Aditya V, Rajesh R (2020)\u00a0Hand gestures for emergency situations: A video dataset based on words from Indian sign language.Data in Brief 31. https:\/\/doi.org\/10.1016\/j.dib.2020.106016","DOI":"10.1016\/j.dib.2020.106016"},{"key":"14084_CR3","doi-asserted-by":"publisher","first-page":"83199","DOI":"10.1109\/ACCESS.2020.2990699","volume":"8","author":"S Aly","year":"2020","unstructured":"Aly S, Aly W (2020) Deep ArSLR: A Novel Signer-Independent Deep Learning Framework for Isolated Arabic Sign Language Gestures Recognition. IEEE Access 8:83199\u201383212","journal-title":"IEEE Access"},{"key":"14084_CR4","doi-asserted-by":"publisher","unstructured":"Ansari MA, Singh DK (2019) An approach for human machine interaction using dynamic hand gesture recognition. In: 2019 IEEE Conference on Information and Communication Technology, pp 1\u20136. https:\/\/doi.org\/10.1109\/CICT48419.2019.9066173","DOI":"10.1109\/CICT48419.2019.9066173"},{"key":"14084_CR5","doi-asserted-by":"publisher","unstructured":"Aparna C, Geetha M (2020) CNN and stacked LSTM model for Indian sign language recognition. Machine Learning and Metaheuristics Algorithms, and Applications, 126\u2013134. https:\/\/doi.org\/10.1007\/978-981-15-4301-2_10","DOI":"10.1007\/978-981-15-4301-2_10"},{"key":"14084_CR6","doi-asserted-by":"publisher","unstructured":"Athira PK, Sruthi CJ, Lijiya A (2019)\u00a0Signer independent sign language recognition with co-articulation elimination from live videos: an indian scenario.Journal of King Saud University - Computer and Information Sciences 34(3):771\u2013781.https:\/\/doi.org\/10.1016\/j.jksuci.2019.05.002","DOI":"10.1016\/j.jksuci.2019.05.002"},{"key":"14084_CR7","doi-asserted-by":"publisher","unstructured":"Bhatti UA, Huang M, Wang H, Zhang Y, Mehmood A, Di W (2018) Recommendation system for immunization coverage and monitoring. Hum Vaccin Immunother 14(1):165\u2013171. https:\/\/doi.org\/10.1080\/21645515.2017.1379639","DOI":"10.1080\/21645515.2017.1379639"},{"issue":"3","key":"14084_CR8","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1080\/17517575.2018.1557256","volume":"13","author":"UA Bhatti","year":"2019","unstructured":"Bhatti UA, Huang M, Zhang DWY, Mehmood A, Han H (2019) Recommendation system using feature extraction and pattern recognition in clinical care systems. Enterp Inf Syst 13(3):329\u2013351","journal-title":"Enterp Inf Syst"},{"key":"14084_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2021.3090410","volume":"Volume: 60","author":"UA Bhatti","year":"2021","unstructured":"Bhatti UA, Yu Z, Chanussot J, Zeeshan Z, Yuan L, Luo W, Nawaz SA, Bhatti MA, Ain QU, Mehmood A (2021) Local Similarity-Based Spatial\u2013Spectral Fusion Hyperspectral Image Classification with Deep CNN and Gabor Filtering. IEEE Trans Geosci Remote Sens Volume: 60:1\u201315","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"14084_CR10","doi-asserted-by":"publisher","unstructured":"Bhatti UA, Zeeshan Z, Nizamani MM, Bazai S, Yu Z, Yuan L (2022) Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19. Chemosphere 288(Pt 2):132569. https:\/\/doi.org\/10.1016\/j.chemosphere.2021.132569","DOI":"10.1016\/j.chemosphere.2021.132569"},{"issue":"9","key":"14084_CR11","doi-asserted-by":"publisher","first-page":"10445","DOI":"10.1109\/JSEN.2021.3061608","volume":"21","author":"SD Breland","year":"2021","unstructured":"Breland SD, Skriubakken SB, Dayal A, Jha A, Yalavarthy PK (2021) Deep Learning-Based Sign Language Digits Recognition from Thermal Images with Edge Computing System. IEEE Sens J 21(9):10445\u201310453","journal-title":"IEEE Sens J"},{"key":"14084_CR12","doi-asserted-by":"publisher","unstructured":"Cai Y\u00a0et al (2021) YOLOv4-5D: An Effective and Efficient Object Detector for Autonomous Driving. IEEE Trans Instrum Meas 70:1\u201313. https:\/\/doi.org\/10.1109\/TIM.2021.3065438","DOI":"10.1109\/TIM.2021.3065438"},{"issue":"18","key":"14084_CR13","doi-asserted-by":"publisher","first-page":"5162","DOI":"10.3390\/s20185162","volume":"20","author":"CL Chowdhary","year":"2020","unstructured":"Chowdhary CL, Patel PV, Kathrotia KJ, Perumal MAK, Ijaz MF (2020) Analytical study of hybrid techniques for image encryption and decryption. Sensors 20(18):5162","journal-title":"Sensors"},{"key":"14084_CR14","doi-asserted-by":"crossref","unstructured":"Das S, Biswas SK, Chakaraborty M, Purkayastha B (2022) \u201cA Review on Sign Language Recognition (SLR) System: ML and DL for SLR\u201d, IEEE Int Conf Intell Syst, Smart Green Technol (ICISSGT), pp. 177\u2013182","DOI":"10.1109\/ICISSGT52025.2021.00045"},{"key":"14084_CR15","doi-asserted-by":"crossref","unstructured":"Das S Das S, Biswas SK, Chakaraborty M, Purkayastha B (2022) \u201cIntelligent Indian Sign Language Recognition Systems: A Critical Review\u201d, ICT Syst Sustain, pp. 703\u2013713","DOI":"10.1007\/978-981-16-5987-4_71"},{"key":"14084_CR16","doi-asserted-by":"crossref","unstructured":"Dhingra, N, Kunz, A (2019) Res3atn - deep 3D residual attention network for hand gesture recognition in videos. In 2019 international conference on 3D vision (3DV) (pp. 491\u2013501)","DOI":"10.1109\/3DV.2019.00061"},{"key":"14084_CR17","doi-asserted-by":"crossref","unstructured":"Dutta KK, Bellary S (2017) \u201cMachine Learning Techniques for Indian Sign Language Recognition\u201d, Int Conf Current Trends Comput Electr Electron Commun (ICCTCEEC), pp. 333\u2013336","DOI":"10.1109\/CTCEEC.2017.8454988"},{"issue":"12","key":"14084_CR18","doi-asserted-by":"publisher","first-page":"16863","DOI":"10.1007\/s11042-022-12592-x","volume":"81","author":"Y Fang","year":"2022","unstructured":"Fang Y, Liu J, Li J, Cheng J, Hu J, Yi D, Xiao X, Bhatti UA (2022) Robust zero-watermarking algorithm for medical images based on SIFT and Bandelet-DCT. Multimed Tools Appl 81(12):16863\u201316879","journal-title":"Multimed Tools Appl"},{"key":"14084_CR19","doi-asserted-by":"crossref","unstructured":"Gupta B, Shukla P, Mittal A (2016) \u201cK-nearest correlated neighbor classification for Indian sign language gesture recognition using feature fusion\u201d, in International Conference on Computer Communication and Informatics (ICCCI)","DOI":"10.1109\/ICCCI.2016.7479951"},{"key":"14084_CR20","doi-asserted-by":"crossref","unstructured":"Hoang, NN, Lee, G-S, Kim, S-H, Yang, H-J (2018) A real-time multimodal hand gesture recognition via 3D convolutional neural network and key frame extraction. In proceedings of the 2018 international conference on machine learning and machine intelligence (pp. 32\u201337)","DOI":"10.1145\/3278312.3278314"},{"key":"14084_CR21","doi-asserted-by":"crossref","unstructured":"Hore S, Chatterjee S, Santhi V , Dey N, Ashour AS, Balas V, Shi F (2017) \u201cIndian Sign Language Recognition Using Optimized Neural Networks\u201d, Inf Technol Intell Transport Syst, pp. 553\u2013563","DOI":"10.1007\/978-3-319-38771-0_54"},{"issue":"23","key":"14084_CR22","doi-asserted-by":"publisher","first-page":"4941","DOI":"10.3390\/rs13234941","volume":"13","author":"R Hussain","year":"2021","unstructured":"Hussain R, Karbhari Y, Ijaz MF, Wo\u017aniak M, Singh PK, Sarkar R (2021) Revise-net: exploiting reverse attention mechanism for salient object detection. Remote Sens 13(23):4941","journal-title":"Remote Sens"},{"issue":"2","key":"14084_CR23","first-page":"952","volume":"25","author":"MH Ismail","year":"2022","unstructured":"Ismail MH, Dawwd SA, Ali FH (2022) Dynamic hand gesture recognition of Arabic sign language by using deep convolutional neural networks. Ind J Electr Eng Comput Sci 25(2):952\u2013962","journal-title":"Ind J Electr Eng Comput Sci"},{"issue":"5","key":"14084_CR24","doi-asserted-by":"publisher","first-page":"123","DOI":"10.18178\/ijmlc.2017.7.5.633","volume":"7","author":"T Janani","year":"2017","unstructured":"Janani T, Ramanan A (2017) Feature Fusion for Efficient Object Classification Using Deep and Shallow Learning. Int J Mach Learn Comput 7(5):123\u2013127","journal-title":"Int J Mach Learn Comput"},{"key":"14084_CR25","doi-asserted-by":"publisher","unstructured":"Jayadeep G, Vishnupriya NV, Venugopal V, Vishnu S, Geetha M (2020) Mudra: convolutional neural network based indian sign language translator for banks. In:\u00a02020 4th International Conference on Intelligent Computing and Control Systems (ICICCS), pp 1228\u20131232. https:\/\/doi.org\/10.1109\/ICICCS48265.2020.9121144","DOI":"10.1109\/ICICCS48265.2020.9121144"},{"key":"14084_CR26","doi-asserted-by":"publisher","unstructured":"Kaur P, Kumar Y, Ahmed S, Alhumam A, Singla R\u00a0et al (2022) Automatic license plate recognition system for vehicles using a cnn. Comput Mater Contin 71(1):35\u201350. https:\/\/doi.org\/10.32604\/cmc.2022.017681","DOI":"10.32604\/cmc.2022.017681"},{"key":"14084_CR27","doi-asserted-by":"publisher","unstructured":"Tareen SAK, Saleem Z (2018) A comparative analysis of SIFT, SURF, KAZE, AKAZE, ORB, and BRISK. In:\u00a02018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), pp 1\u201310. https:\/\/doi.org\/10.1109\/ICOMET.2018.8346440","DOI":"10.1109\/ICOMET.2018.8346440"},{"key":"14084_CR28","doi-asserted-by":"crossref","unstructured":"Kumar NKS, Malarvizhi N (2020) Bi-directional LSTM\u2013CNN combined method for sentiment analysis in part of speech tagging (PoS). Int J Speech Technol 23(373\u2013380)","DOI":"10.1007\/s10772-020-09716-9"},{"key":"14084_CR29","doi-asserted-by":"publisher","unstructured":"Kumar P, Gauba H, Roy PP, Dogra DP (2017)\u00a0A multimodal framework for sensor based sign language recognition.Neurocomputing 259:21\u201338. https:\/\/doi.org\/10.1016\/j.neucom.2016.08.132","DOI":"10.1016\/j.neucom.2016.08.132"},{"key":"14084_CR30","doi-asserted-by":"publisher","unstructured":"Alzubaidi L et al (2021)\u00a0Review of deep learning: concepts, CNN architectures, challenges, applications, future directions. J Big Data 8:53. https:\/\/doi.org\/10.1186\/s40537-021-00444-8","DOI":"10.1186\/s40537-021-00444-8"},{"key":"14084_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.eswa.2021.115543","volume":"Volume: 184","author":"Y Li","year":"2021","unstructured":"Li Y, Cai Y, Malekian R, Wang H, Sotelo MA, Li Z (2021) Creating navigation map in semi-open scenarios for intelligent vehicle localization using multi-sensor fusion. Exp Syst Appl Volume: 184:1\u201312","journal-title":"Exp Syst Appl"},{"key":"14084_CR32","first-page":"1","volume":"Volume: 24","author":"T Li","year":"2022","unstructured":"Li T, Li J, Liu J, Huang M, Chen YW, Bhatti UA (2022) Robust watermarking algorithm for medical images based on log-polar transform. EURASIP J Wireless Commun Netw Volume: 24:1\u201311","journal-title":"EURASIP J Wireless Commun Netw"},{"key":"14084_CR33","doi-asserted-by":"crossref","unstructured":"Likhar P, Bhagat NK, Rathna GN (2020) \u201cDeep learning methods for Indian sign language recognition\u201d,10th International Conference on Consumer Electronics (ICCE-Berlin)","DOI":"10.1109\/ICCE-Berlin50680.2020.9352194"},{"key":"14084_CR34","doi-asserted-by":"publisher","unstructured":"Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60:91\u2013110. https:\/\/doi.org\/10.1023\/B:VISI.0000029664.99615.94","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"issue":"16","key":"14084_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/JSEN.2019.2909837","volume":"19","author":"A Mittal","year":"2019","unstructured":"Mittal A, Kumar P, Roy PP, Balasubramanian R, Chaudhuri BB (2019) A modified-LSTM model for continuous sign language recognition using leap motion. IEEE Sens J 19(16):1\u20138","journal-title":"IEEE Sens J"},{"key":"14084_CR36","doi-asserted-by":"publisher","unstructured":"Nanni L, Ghidoni S, Brahnam S (2017)\u00a0Handcrafted vs. non-handcrafted features for computer vision classification,Pattern Recogn 71:158\u2013172.https:\/\/doi.org\/10.1016\/j.patcog.2017.05.025","DOI":"10.1016\/j.patcog.2017.05.025"},{"key":"14084_CR37","doi-asserted-by":"crossref","unstructured":"Nawaz SA, Li J, Bhatti UA, Bazai SU, Zafar A, Bhatti MA, Mehmood A, Ain Q, Shoukat MU (2021) A hybrid approach to forecast the COVID-19 epidemic trend. Plos One 16(10):1\u201316","DOI":"10.1371\/journal.pone.0256971"},{"key":"14084_CR38","doi-asserted-by":"publisher","unstructured":"Rastgoo R, Kiani K, Escalera S (2020)\u00a0Hand sign language recognition using multi-view hand skeleton.\u00a0Expert Syst Appl 150:113336.https:\/\/doi.org\/10.1016\/j.eswa.2020.113336","DOI":"10.1016\/j.eswa.2020.113336"},{"key":"14084_CR39","doi-asserted-by":"publisher","unstructured":"Rastgoo R, Kiani K, Escalera S (2021) Sign language recognition: a deep survey.\u00a0Expert Syst Appl\u00a0164:113794.https:\/\/doi.org\/10.1016\/j.eswa.2020.113794","DOI":"10.1016\/j.eswa.2020.113794"},{"key":"14084_CR40","doi-asserted-by":"crossref","unstructured":"Rastgoo R, Kiani K, Escalera S (2021) Sign language recognition: a deep survey. Expert Syst Appl, [ISSN: 0957-4174] 164(113794):1\u201327","DOI":"10.1016\/j.eswa.2020.113794"},{"key":"14084_CR41","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cviu.2020.102949","volume":"195","author":"E Saraee","year":"2020","unstructured":"Saraee E, Jalal M, Betke M (2020) Visual complexity analysis using deep intermediate-layer features. Comput Vis Image Underst 195:1\u201317","journal-title":"Comput Vis Image Underst"},{"key":"14084_CR42","doi-asserted-by":"crossref","unstructured":"Shaik KB, Ganesan P, Kalist V, Sathish BS, Jenitha JM (2015) \u201cComparative Study of Skin Color Detection and Segmentation in HSV and YCbCr Color Space\u201d, Int Conf Recent Trends Computing (ICRTC), pp.41\u201348","DOI":"10.1016\/j.procs.2015.07.362"},{"key":"14084_CR43","doi-asserted-by":"crossref","unstructured":"Singh DK (2021) \u201c3D-CNN based Dynamic Gesture Recognition for Indian Sign Language Modeling\u201d, Int Conf AI Comput Linguist, pp. 76\u201383","DOI":"10.1016\/j.procs.2021.05.071"},{"key":"14084_CR44","doi-asserted-by":"crossref","unstructured":"Sonare B, Padgal A, Gaikwad Y, Patil A (2021) \u201cVideo-Based Sign Language Translation System Using Machine Learning\u201d, 2nd International Conference for Emerging Technology (INCET), pp. 1\u20134","DOI":"10.1109\/INCET51464.2021.9456176"},{"key":"14084_CR45","doi-asserted-by":"publisher","unstructured":"Sridhar A, Ganesan RG, Kumar P, Khapra M (2020) INCLUDE: A Large Scale Dataset for Indian Sign Language Recognition. In: Proceedings of the 28th ACM International Conference on Multimedia. Association for Computing Machinery, Seattle, pp 1366\u20131375. https:\/\/doi.org\/10.1145\/3394171.3413528","DOI":"10.1145\/3394171.3413528"},{"key":"14084_CR46","doi-asserted-by":"publisher","first-page":"18762","DOI":"10.1109\/ACCESS.2021.3054250","volume":"Volume:9","author":"J Tamang","year":"2021","unstructured":"Tamang J, Nkapkop JDD, Ijaz MF, Prasad PK, Tsafack N, Saha A, Kengne J, Son Y (2021) Dynamical properties of ion-acoustic waves in space plasma and its application to image encryption. IEEE Access Volume:9:18762\u201318782","journal-title":"IEEE Access"},{"key":"14084_CR47","doi-asserted-by":"publisher","unstructured":"Taskiran M, Killioglu M, Kahraman N (2018) A real-time system for recognition of american sign language by using deep learning. In:\u00a02018 41st International Conference on Telecommunications and Signal Processing (TSP),\u00a0pp 1\u20135. https:\/\/doi.org\/10.1109\/TSP.2018.8441304","DOI":"10.1109\/TSP.2018.8441304"},{"key":"14084_CR48","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.eswa.2021.115601","volume":"Volume 185","author":"A Venugopalan","year":"2021","unstructured":"Venugopalan A, Reghunadhan R (2021) Applying deep neural networks for the automatic recognition of sign language words: A communication aid to deaf agriculturists. Expert Syst Appl Volume 185:1\u20139","journal-title":"Expert Syst Appl"},{"key":"14084_CR49","doi-asserted-by":"publisher","first-page":"7957","DOI":"10.1007\/s00521-019-04691-y","volume":"Volume 32","author":"A Wadhawan","year":"2020","unstructured":"Wadhawan A, Kumar P (2020) Deep learning-based sign language recognition system for static signs. Neural Comput Appl Volume 32:7957\u20137968","journal-title":"Neural Comput Appl"},{"issue":"1511","key":"14084_CR50","first-page":"1","volume":"8","author":"E Zhang","year":"2019","unstructured":"Zhang E, Botao X, Fangzhou C, Jinghong D, Guangfeng L, Yifei L (2019) Fusion of 2D CNN and 3D densenet for dynamic gesture recognition. Electron 8(1511):1\u201315","journal-title":"Electron"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-14084-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-14084-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-14084-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,15]],"date-time":"2023-04-15T09:24:02Z","timestamp":1681550642000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-14084-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,29]]},"references-count":50,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2023,5]]}},"alternative-id":["14084"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-14084-4","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,29]]},"assertion":[{"value":"17 May 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 August 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 October 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 October 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}