SRCNN: Stacked-Residual Convolutional Neural Network for Improving Human Activity Classification Based on Micro-Doppler Signatures of FMCW Radar
Current methods for daily human activity classification primarily rely on optical images from cameras or wearable sensors. Despite their high detection reliability, camera-based approaches suffer from several drawbacks, such as low-light conditions, limited range, and privacy concerns. To address th...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The Korean Institute of Electromagnetic Engineering and Science
2024-07-01
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| Series: | Journal of Electromagnetic Engineering and Science |
| Subjects: | |
| Online Access: | https://jees.kr/upload/pdf/jees-2024-4-r-235.pdf |
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