A Lightweight CNN Approach for Hand Gesture Recognition via GAF Encoding of A-Mode Ultrasound Signals

Hand gesture recognition(HGR) is a key technology in human-computer interaction and human communication. This paper presents a lightweight, parameter-free attention convolutional neural network (LPA-CNN) approach leveraging Gramian Angular Field(GAF)transformation of A-mode ultrasound signals for HG...

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Detalles Bibliográficos

Principais autores:	Qican Shangguan, Yue Lian, Zhiwei Liao, Jinshui Chen, Yiru Song, Ligang Yao, Cai Jiang, Zongxing Lu, Zhonghua Lin
Formato:	Artigo
Idioma:	Inglês
Publicado:	IEEE 2025-01-01
Series:	IEEE Transactions on Neural Systems and Rehabilitation Engineering
Assuntos:	A-mode ultrasound convolutional neural network (CNN) deep learning hand gesture recognition (HGR) gramian angular field (GAF)
Acceso en liña:	https://ieeexplore.ieee.org/document/11156155/
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