Design of an efficient spiking neural network for human activity recognition
Human activity recognition (HAR) using Wi-Fi Channel State Information (CSI) has attracted significant interest as an alternative to conventional methods due to its potential to address human privacy concerns. While Long Short-Term Memory (LSTM) models have shown promising results in HAR, their reso...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2024
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| Online Access: | http://eprints.utem.edu.my/id/eprint/27405/1/Design%20of%20an%20efficient%20spiking%20neural%20network%20for%20human%20activity%20recognition.pdf http://eprints.utem.edu.my/id/eprint/27405/2/Design%20of%20an%20efficient%20spiking%20neural%20network%20for%20human%20activity%20recognition.pdf |
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http://eprints.utem.edu.my/id/eprint/27405/1/Design%20of%20an%20efficient%20spiking%20neural%20network%20for%20human%20activity%20recognition.pdfhttp://eprints.utem.edu.my/id/eprint/27405/2/Design%20of%20an%20efficient%20spiking%20neural%20network%20for%20human%20activity%20recognition.pdf