Effects of sliding window variation in the performance of acceleration-based human activity recognition using deep learning models | Zendy

Milagros Jaén-Vargas | Zendy; Karla Miriam Reyes Leiva | Zendy; Francisco Fernandes | Zendy; Sérgio Barroso Gonçalves | Zendy; Miguel Tavares Silva | Zendy; Daniel Simões Lopes | Zendy; José Javier Serrano Olmedo | Zendy

Open Access

Effects of sliding window variation in the performance of acceleration-based human activity recognition using deep learning models

Author(s) -

Milagros Jaén-Vargas,

Karla Miriam Reyes Leiva,

Francisco Fernandes,

Sérgio Barroso Gonçalves,

Miguel Tavares Silva,

Daniel Simões Lopes,

José Javier Serrano Olmedo

Publication year - 2022

Publication title -

peerj computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.806

H-Index - 24

ISSN - 2376-5992

DOI - 10.7717/peerj-cs.1052

Subject(s) - computer science , sliding window protocol , convolutional neural network , artificial intelligence , acceleration , preprocessor , deep learning , pattern recognition (psychology) , inertial measurement unit , artificial neural network , feature extraction , f1 score , feature (linguistics) , window (computing) , linguistics , philosophy , physics , classical mechanics , operating system

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