From Movements to Metrics: Evaluating Explainable AI Methods in Skeleton-Based Human Activity Recognition
The advancement of deep learning in human activity recognition (HAR) using 3D skeleton data is critical for applications in healthcare, security, sports, and human–computer interaction. This paper tackles a well-known gap in the field, which is the lack of testing in the applicability and reliabilit...
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| Huvudupphov: | , , |
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| Materialtyp: | Artigo |
| Språk: | Inglês |
| Utgiven: |
MDPI AG
2024-03-01
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| Serie: | Sensors |
| Ämnen: | |
| Länkar: | https://www.mdpi.com/1424-8220/24/6/1940 |
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