Enhancing sign language recognition using CNN and SIFT: A case study on Pakistan sign language
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Published:2024-02
Issue:2
Volume:36
Page:101934
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ISSN:1319-1578
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Container-title:Journal of King Saud University - Computer and Information Sciences
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language:en
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Short-container-title:Journal of King Saud University - Computer and Information Sciences
Author:
Arooj Sadia,
Altaf SaudORCID,
Ahmad Shafiq,
Mahmoud HaithamORCID,
Mohamed Adamali Shah Noor
Funder
King Saud University
Reference32 articles.
1. Ahuja, M. K., & Singh, A. (2016). Static vision based Hand Gesture recognition using principal component analysis. In Proceedings of the 2015 IEEE 3rd International Conference on MOOCs, Innovation and Technology in Education, MITE 2015, 402–406.
2. Hand gesture recognition for sign language using 3DCNN;Al-Hammadi;IEEE Access,2020
3. A real time arabic sign language alphabets (ArSLA) recognition model using deep learning architecture;Alsaadi;Computers,2022
4. A comparative review on applications of different sensors for sign language recognition;Amin;Journal of Imaging,2022
5. A pseudo-softmax function for hardware-based high speed image classification;Cardarilli;Sci. Rep.,2021
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