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...
| المؤلف الرئيسي: | |
|---|---|
| التنسيق: | أطروحة |
| اللغة: | الإنجليزية الإنجليزية |
| منشور في: |
2024
|
| الوصول للمادة أونلاين: | 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 |
الانترنت
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