Fall detection algorithm based on pyramid network and feature fusion

Accidental falls are the second leading cause of accidental death of the elderly. Early intervention measures can reduce the problem. However, so far, there are few related studies using Transformer coding module for fall detection feature extraction, and the real-time performance of existing algori...

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Vydáno v:	Evolving systems Ročník 15; číslo 5; s. 1957 - 1970
Hlavní autoři:	Li, Jiangjiao, Gao, Mengqi, Wang, Peng, Li, Bin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2024 Springer Nature B.V
Témata:	Accelerometers Accuracy Algorithms Artificial Intelligence Artificial neural networks Classification Complex Systems Complexity Datasets Deep learning Engineering Fall detection Feature extraction Feature recognition Machine learning Methods Modules Neural networks Older people Original Paper Performance evaluation Real time Sensors Smartwatches Transformers Wearable computers Pyramid network Feature fusion Transformer Gate recurrent unit Fall detection
ISSN:	1868-6478, 1868-6486
On-line přístup:	Získat plný text
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