Advancing human activity recognition with quaternion-based recurrent neural networks

Advancing human activity recognition with quaternion-based recurrent neural networks

Human activity recognition (HAR) stands as a vital nexus in the synthesis of healthcare, sports analytics, and human–computer interaction. This research introduces a groundbreaking approach to HAR by amalgamating the multidimensional strengths of quaternion algebra with the temporal sensitivity of r...

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Bibliographic Details
Main Authors: S. Gayathri Devi, Ratnala Venkata Siva Harish, N. Nalini, K. D. V. Prasad, N. Nagabhooshanam
Format: Article
Language:English
Published: Taylor & Francis Group 2025-07-01
Series:Automatika
Subjects:
HHuman activity recognition
quaternion algebra
recurrent neural networks
wearable technology
multidimensional sequencing
temporal dependencies
Online Access:https://www.tandfonline.com/doi/10.1080/00051144.2025.2480419
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https://www.tandfonline.com/doi/10.1080/00051144.2025.2480419

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