Human Action Representation Learning Using an Attention-Driven Residual 3DCNN Network

Human Action Representation Learning Using an Attention-Driven Residual 3DCNN Network

The recognition of human activities using vision-based techniques has become a crucial research field in video analytics. Over the last decade, there have been numerous advancements in deep learning algorithms aimed at accurately detecting complex human actions in video streams. While these algorith...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Hayat Ullah, Arslan Munir
Format: Artykuł
Język:English
Wydane: MDPI AG 2023-07-01
Seria:Algorithms
Hasła przedmiotowe:
human activity recognition
3DCNN
3D spatial attention
3D channel attention
residual convolutional neural network
pattern recognition
Dostęp online:https://www.mdpi.com/1999-4893/16/8/369

Internet

https://www.mdpi.com/1999-4893/16/8/369

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