Table 2.
The classification comparation on the UCI and WISDM datasets.
Models | Accuracy (%) | Accuracy (%) |
---|---|---|
on UCI | on WISDM | |
Inherent Features-based CNN4 | 91.75 | 91.50 |
Coherent Features-based CNN5 | 92.31 | 92.20 |
HAR-image CNN7 | 93.27 | 91.64 |
Multi-stage CNN10 | 94.29 | 93.19 |
Attention-based Multi-head CNN9 | 95.62 | 94.90 |
Temporal CNN6 | 96.31 | 95.71 |
Feature Embedding-based LSTM16 | 96.31 | 95.55 |
ConvAE-LSTM21 | 96.41 | 95.60 |
Attention-based LSTM22 | 95.18 | 93.74 |
Hybrid CNN and LSTM17 | 96.55 | 95.65 |
Proposed Method | 96.71 | 95.86 |