Deep neural networks for human activity recognition with wearable sensors: Leave-one-subject-out cross-validation for model selection

D Gholamiangonabadi, N Kiselov, K Grolinger - Ieee Access, 2020 - ieeexplore.ieee.org
Human Activity Recognition (HAR) has been attracting significant research attention
because of the increasing availability of environmental and wearable sensors for collecting …
被引用次数：124 相关文章

[引用][C] Deep Neural Networks for Human Activity Recognition With Wearable Sensors: Leave-One-Subject-Out Cross-Validation for Model Selection

D Gholamiangonabadi, N Kiselov, K Grolinger - IEEE Access, 2020 - cir.nii.ac.jp
Deep Neural Networks for Human Activity Recognition With Wearable Sensors: Leave-One-Subject-Out
Cross-Validation for Model Selection | CiNii Research CiNii 国立情報学研究所 学術情報 …
[PDF] academia.edu

[PDF][PDF] Deep Neural Networks for Human Activity Recognition With Wearable Sensors: Leave-One-Subject-Out Cross-Validation for Model Selection

D GHOLAMIANGONABADI, N KISELOV - academia.edu
ABSTRACT Human Activity Recognition (HAR) has been attracting significant research
attention because of the increasing availability of environmental and wearable sensors for …

[引用][C] Deep Neural Networks for Human Activity Recognition With Wearable Sensors: Leave-One-Subject-Out Cross-Validation for Model Selection

D Gholamiangonabadi, N Kiselov… - IEEE Access, 2020 - ui.adsabs.harvard.edu
Deep Neural Networks for Human Activity Recognition With Wearable Sensors: Leave-One-Subject-Out
Cross-Validation for Model Selection - NASA/ADS Now on home page ads icon ads Enable …