HIGHLIGHTS
- who: Md Shafiqul Islam et al. from the Department of Electronics Engineering, University, Seoul, Republic of Korea have published the paper: STC-NLSTMNet: An Improved Human Activity Recognition Method Using Convolutional Neural Network with NLSTM from WiFi CSI, in the Journal: Sensors 2023, 356 of 17/Nov/2022
- what: Motivated by this the authors propose a novel DL-based model named spatio-temporal convolution with nested long short-term memory (STCNLSTMNet) with the ability to extract spatial and temporal features concurrently and automatically recognize human activity with very high accuracy. The authors propose a model . . .
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