SLRNetwork: Utilizing Skip Connections for Better Feature Extraction in Recognition of Sign Languages to Help Mutism
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-2742-5_24
Reference12 articles.
1. Kasapbaşi A, Ahmed Elbushra AE, Al-Hardanee O, Yilmaz A (2022) DeepASLR: a CNN based human computer interface for American Sign Language recognition for hearing-impaired individuals. Comput Methods Programs Biomed 2:100048
2. Koller O, Ney H, Bowden R (2016) Deep hand: how to train a CNN on 1 million hand images when your data is continuous and weakly labeled. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3793–3802
3. Koller O, Zargaran O, Ney H, Bowden R (2016) Deep sign: hybrid CNN-hmm for continuous sign language recognition. In: Proceedings of the British machine vision conference
4. Cui R, Liu H, Zhang C (2017) Recurrent convolutional neural networks for continuous sign language recognition by staged optimization. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7361–7369
5. Pu J, Zhou W, Li H (2019) Iterative alignment network for continuous sign language recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4165–4174
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