ref [8] · 2509.03467 · notice #8506 · dispute
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ArabSign: A multi-modality dataset and benchmark for continuous Arabic sign language recognition. arXiv preprint arXiv:2210.03951, 2022. 21 A PREPRINT - S EPTEMBER 10, 2025 [8] M. M. Balaha, S. El-Kady, H. M. Balaha, M. Salama, E. Emad, M. Hassan, and M. M. Saafan. A vision-based deep learning approach for independent-users Arabic sign language interpretation. Multimedia Tools and Applications, 82(5):6807-6826, 2023. doi:10.1007/s11042-022-13423-9. [9] N. Alkhalifa et al. Continuous Arabic sign language recognition models. Sensors, 25(9):2916, 2025. doi:10.3390/s25092916. [10] M. Al-Hammadi et al. Deep learning-based approach for sign language gesture recognition with efficient hand gesture representation. IEEE Access, 8:192527-192542, 2021. doi:10.1109/ACCESS.2020.3031440. [11] G. Batnasan, M.
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ArabSign: A multi-modality dataset and benchmark for continuous Arabic sign language recognition. arXiv preprint arXiv:2210.03951, 2022. 21 A PREPRINT - S EPTEMBER 10, 2025 [8] M. M. Balaha, S. El-Kady, H. M. Balaha, M. Salama, E. Emad, M. Hassan, and M. M. Saafan. A vision-based deep learning approach for independent-users Arabic sign language interpretation. Multimedia Tools and Applications, 82(5):6807-6826, 2023. doi:10.1007/s11042-022-13423-9. [9] N. Alkhalifa et al. Continuous Arabic sign language recognition models. Sensors, 25(9):2916, 2025. doi:10.3390/s25092916. [10] M. Al-Hammadi et al. Deep learning-based approach for sign language gesture recognition with efficient hand gesture representation. IEEE Access, 8:192527-192542, 2021. doi:10.1109/ACCESS.2020.3031440. [11] G. Batnasan, M