Applying MLP-Mixer and gMLP to Human Activity Recognition
Applying MLP-Mixer and gMLP to Human Activity Recognition
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Publisher
Switzerland: MDPI AG
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Language
English
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Switzerland: MDPI AG
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The development of deep learning has led to the proposal of various models for human activity recognition (HAR). Convolutional neural networks (CNNs), initially proposed for computer vision tasks, are examples of models applied to sensor data. Recently, high-performing models based on Transformers and multi-layer perceptrons (MLPs) have also been p...
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Full title
Applying MLP-Mixer and gMLP to Human Activity Recognition
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TN_cdi_doaj_primary_oai_doaj_org_article_2ed1f4f5eddf43c2a3d41687833fae38
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2ed1f4f5eddf43c2a3d41687833fae38
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ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s25020311
