Sign Language Recognition Based on CNN-BiLSTM Using RF Signals

As the number of individuals with speech and hearing impairments continues to grow, the demand for sign language recognition systems is increasing. Furthermore, most radio frequency-based gesture recognition systems have primarily focused on simple gestures, neglecting more complex actions such as s...

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Veröffentlicht in:	IEEE access Jg. 12; S. 190487 - 190504
Hauptverfasser:	Zhang, Yajun, Wang, Yuankang, Li, Feng, Yu, Weiqian, Wang, Congcong, Jiang, Ying
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Algorithms Antenna arrays Artificial neural networks Assistive technologies Background noise BiLSTM Cameras CNN Feature extraction Gesture recognition Noise Radio frequency Radio signals Radiofrequency identification RF signals RFID Robustness Segmentation Sign language Sign language recognition Signal reflection signal segmentation Speech recognition Wearable sensors Wireless fidelity
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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