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AUTO-HAR: An adaptive human activity recognition framework using an automated CNN architecture design
Convolutional neural networks (CNNs) have demonstrated exceptional results in the analysis of time- series data when used for Human Activity Recognition (HAR). The manual design of such neural architectures is an error-prone and time-consuming process. The search for optimal CNN architectures is con...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9958436/ https://www.ncbi.nlm.nih.gov/pubmed/36852018 http://dx.doi.org/10.1016/j.heliyon.2023.e13636 |