Real-Time Hand Gesture Recognition for American Sign Language Using CNN, Mediapipe and Convexity Approach
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-62217-5_22
Reference12 articles.
1. Anderson, R., Wiryana, F., Ariesta, M.C., Kusuma, G.P., et al.: Sign language recognition application systems for deaf-mute people: a review based on input-process-output. Procedia Comput. Sci. 116, 441–448 (2017)
2. Puchakayala, A., Nalla, S., Pranathi, K.: American sign language recognition using deep learning. In: 2023 7th International Conference on Computing Methodologies and Communication (ICCMC), pp. 151–155. IEEE (2023)
3. Chu, X., Liu, J., Shimamoto, S.: A sensor-based hand gesture recognition system for japanese sign language. In: 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech), pp. 311–312. IEEE (2021)
4. Yuanyuan, S.H.I., Yunan, L.I., Xiaolong, F.U., Kaibin, M.I.A.O., Qiguang, M.I.A.O.: Review of dynamic gesture recognition. Virtual Reality Intell. Hardw. 3(3), 183–206 (2021)
5. Barros, P., Maciel-Junior, N.T., Fernandes, B.J.T., Bezerra, B.L.D., Fernandes, S.M.M.: A dynamic gesture recognition and prediction system using the convexity approach. Comput. Vision Image Understand. 155, 139–149 (2017)
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