Human motion recognition based on feature fusion and residual networks
Abstract Addressing the issue of low recognition accuracy in human motion detection when relying on a single feature, a novel approach integrating Frequency Modulated Continuous Wave (FMCW) radar technology with a Residual Network (ResNet) architecture has been proposed. This method commences by cap...
Saved in:
| Main Authors: | Xiaoyu Luo, Qiusheng Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-80783-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
GAN-Based Driver’s Head Motion Using Millimeter-Wave Radar Sensor
by: Hong Nhung Nguyen, et al.
Published: (2025-01-01) -
Indoor Human Motion Recognition Based on FMCW Radar and Threshold Comparison Algorithm
by: Ruoyu He, et al.
Published: (2025-01-01) -
Complying with the EU AI Act: Innovations in explainable and user-centric hand gesture recognition
by: Sarah Seifi, et al.
Published: (2025-06-01) -
Radar-Based Activity Recognition in Strictly Privacy-Sensitive Settings Through Deep Feature Learning
by: Giovanni Diraco, et al.
Published: (2025-04-01) -
A few-shot learning-based dual-input neural network for complex spectrogram recognition system with millimeter-wave radar
by: Kaiyu Chen, et al.
Published: (2025-04-01)