Open Access
Issue |
ITM Web Conf.
Volume 57, 2023
Fifth International Conference on Advances in Electrical and Computer Technologies 2023 (ICAECT 2023)
|
|
---|---|---|
Article Number | 01019 | |
Number of page(s) | 13 | |
Section | Software Engineering & Information Technology | |
DOI | https://doi.org/10.1051/itmconf/20235701019 | |
Published online | 10 November 2023 |
- A.A. Bar Bhuiya, R.K. Karsh, R. Jain “CNN based feature extraction and classification for sign language” Multimedia Tools and Applications, 80 (2) (2021), pp. 3051-3069. [CrossRef] [Google Scholar]
- Shruty M. Tomar, Dr.Narendra M. Patel, Dr.Darshak G. Thakore. A Survey on Sign Language RecognitionSystems. IJCRT, Volume 9, Issue 3 March 2021. [Google Scholar]
- Sandrine Tor Nay, Marzieh Razavi, Mathew Magimai-Doss “Towards multilingual sign language recognition” Proceedings of the ICASSP, IEEE international conference on acoustics, speech and signal processing (2020), pp. 6309-6313 [Google Scholar]
- Shirbhate, Radha S., Mr.Vedant D. Shinde, Ms.Sanam A. Metkari, Ms.Pooja U. Borkar and Ms.Mayuri A. Khandge. “Sign language Recognition Using Machine Learning Algorithm.” Volume: 07 Issue: 03 Mar 2020 [Google Scholar]
- D. M. M. T. Ankur Verma, Gaurav Dubey, “Sign Language Translator”, IJAST, vol. 29, no. 5s, pp.246-253, Mar. 2020. [Google Scholar]
- Mehreen Hurroo, Mohammad Elham, 2020, “Sign Language Recognition System using Convolutional Neural Network and Computer Vision”. INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT) Volume 09, Issue 12, 2020 [Google Scholar]
- S.M. Kamal, Y. Chen, S. Li, X. Shi, J. Zheng “Technical approaches to Chinese sign language processing: Areview” IEEE Access, 7 (2019), pp. 96926-96935 [CrossRef] [Google Scholar]
- Steven J. Simske “Introduction, overview, and applications” Meta analytics (2019) [Google Scholar]
- Kshitij Bantupalli, Ying Xie, American sign language recognition using machine learning and computer vision, Master of Science in Computer Science Theses 21 (2019) [Google Scholar]
- Abbas Muhammad Zakariya, Rajni Jindal Published 1 July 2019 Computer Science 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT) [Google Scholar]
- R. G. Rajan and M. J. Leo, “A Comprehensive Analysis on Sign Language, ” International Journal of Recent Technology and Engineering (IJRTE), vol. 7, no. 6, pp. 749-755, 2019. [Google Scholar]
- G. A. Rao and P. V. V. Kishore, “Selfie Sign Language Recognition with Multiple Features on Ada boost Multilabel Multiclass Classifier, ” Journal of Engineering Science and Technology, vol. 13, no. 8, pp. 2352-2368, 2018. [Google Scholar]
- J. Huang, W. Zhou, Q. Zhang, H. Li, and W. Li, “Video-based sign language recognition without temporal segmentation, ” in Proc. AAAI Conf. Artif. Intell., 2018, pp. 1–8. [Google Scholar]
- P. Ravi, “A Review on Image based Indian Sign Language Recognition, ” International Journal of Innovative Research in Computer and Communication Engineering, vol. 6, no. 12, pp. 9101-9107, 2018. [Google Scholar]
- Suharjito, R. Anderson, F. Wiryana, M. C. Ariesta and G. P. Kusuma, “Sign Language Recognition Application Systems for Deaf-Mute People: A Review Based on Input-Process-Output, ” Based on Input-ProcessOutput. Procedia Computer Science, pp. 441-448, 2017. [CrossRef] [Google Scholar]
- S. Bessa Carneiro, E.D.F.D.M. De Santos, T.M.D.A. De Barbosa, J.O. Ferreira, S.G.S.S. Alcala, A.F. Da Rocha Static gestures recognition for Brazilian sign language with Kinect sensor Proceedings of IEEE sensors (2017) [Google Scholar]
- T. Liu, W. Zhou, and H. Li, ‘‘Sign language recognition with long shortterm memory, ’’ in Proc. IEEE Int.Conf. Image Process. (ICIP), Sep. 2016, 925 pp. 2871–2875. [Google Scholar]
- CP.V.V. Kishore, M.V.D. Prasad, C.R. Prasad, R Rahul “4-Camera model for sign language recognition using elliptical Fourier descriptors and ANN” Proceedings of the international conference on signal processing and communication engineering systems, SPACES 2015, in Association with IEEE, (2015), pp. 34-38 [Google Scholar]
- T. Cardoso, J. Delgado and J. Barat, “Hand Gesture Recognition towards Enhancing Accessibility, ” 6th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info exclusion (DSAI 2015), pp. 419-429, 2015. [Google Scholar]
- P. Xanthopoulos, T. Razzaghi “A weighted support vector machine method for control chart patternrecognition”. Computers and Industrial Engineering, 70 (2014), pp. 134-149. [CrossRef] [Google Scholar]
- P. Subha Rajam, DrG. Balakrishnan, ―Real Time Indian Sign Language Recognition System to aid Deaf –Dumb People, 13th IEEE International Conference on Communication Technology (ICCT), Sep 2011, SecretaryGeneral School of Information Science and Engineering, Shandong University, Jinan, Shandong, China. [Google Scholar]
- Nakul Nagpal, DrArun Mitra., DrPankaj Agrawal, “Design Issue and Proposed Implementation of Communication Aid for Deaf & Dumb People”, International Journal on Recent and Innovation Trends in Computing and Communication, Volume: 3 Issue: 5, pp 147–149. [Google Scholar]
- Chandan deep Kaur, Nivit Gill, “An Automated System for Indian Sign Language Recognition”, International Journal of Advanced Research in Computer Science and Software Engineering. [Google Scholar]
- V. Anjana Devi (2011), “Agent Based Cross Layer Intrusion Detection System for MANET”, International conference on Network Security CNSA 2011, ISBN 978-3-64222539-0, pp 427-440. (Springer CCIS). [Google Scholar]
- V. Anjana Devi, ‘Fuzzy Based Decision Model for Detecting Misbehaving Attacks in MANET’, International Journal of Applied Engineering Research, vol. 9, no. 23, pp.20059-20083, 2014. [Google Scholar]
- V. Anjana Devi (2014), ‘ECC Based Malicious Node Detection System for MANET’, Journal of Theoretical and Applied Information Technology, vol. 68, no. 2, pp.239-248. [Google Scholar]
- Anjana Devi V, Arun Syriac, Gogul Kumar (2019), “Efficient Information Retrieval of Encrypted Cloud Data with Ranked Retrieval”, International Conference on International Conference on Emerging Current Trends in Computing and Expert Technology (COMET), vol. 35, pp.229-236. [Google Scholar]
- V. Anjanadevi, Dr.R. Hemalatha, R. Venkateshwar, J. Naren and Dr.G. Vithya (2019), ”A framework for the Diagnosis of Diabetic Retinopathy Using Deep Learning Techniques” International Journal of Psychosocial Rehabilitation, Vol. 23, Issue 01, pp.405-411. [CrossRef] [Google Scholar]
- Anjana Devi V, P.S. Mitra, K. Pooja Dharshini (2020), “HAR system creating a security alert by implementing a deep learning approach “Sambodhi” UGC Care list, Vol. 43, issue. 04. pp.25-30. [Google Scholar]
- Anjana Devi, Nishanthi B and Sai Mahima K (2019), “Transaction Based ECommerce Recommendation Using Collaborative Filtering”, International Conference on Emerging Current Trends in Computing and Expert Technology (COMET) pp. 273-281. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.