FSID: a novel approach to human activity recognition using few-shot weight imprinting
Abstract Accurate recognition of human activities from gait sensory data plays a vital role in healthcare and wellness monitoring. However, conventional deep learning models for Human Activity Recognition (HAR) often require large labeled datasets and extensive training, which limits their effective...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-04323-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|