Pathological-Gait Recognition Using Spatiotemporal Graph Convolutional Networks and Attention Model.

Kim, Jungi; Seo, Haneol; Naseem, Muhammad Tahir; Lee, Chan-Su

Kim, Jungi; Seo, Haneol; Naseem, Muhammad Tahir; Lee, Chan-Su.

Afiliación

Kim J; Department of Automotive Lighting Convergence Engineering, Yeungnam University, Gyeongsan 38541, Korea.
Seo H; Research Institute of Human Ecology, Yeungnam University, Gyeongsan 38541, Korea.
Naseem MT; Research Institute of Human Ecology, Yeungnam University, Gyeongsan 38541, Korea.
Lee CS; Department of Electronic Engineering, Yeungnam University, Gyeongsan 38541, Korea.

Sensors (Basel) ; 22(13)2022 Jun 27.

Article en En | MEDLINE | ID: mdl-35808358

Asunto(s)

Algoritmos; Redes Neurales de la Computación; Marcha; Humanos

Palabras clave

gait classification; global average pooling (GAP); graph convolutional networks (GCN); multiple-input branches (MIB); spatiotemporal graph convolutional networks (ST-GCN); temporal convolutional network (TCN)

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Redes Neurales de la Computación Límite: Humans Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article

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