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pro vyhledávání: '"Sheldon McCall"'
Autor:
Sheldon McCall, Shina Samuel Kolawole, Afreen Naz, Liyun Gong, Syed Waqar Ahmed, Pandey Shourya Prasad, Miao Yu, James Wingate, Saeid Pourroostaei Ardakani
Publikováno v:
IEEE Access, Vol 12, Pp 28798-28809 (2024)
Falls bring about significant risks to individuals’ well-being and independence, prompting widespread public health concerns. Swift detection and even predicting the risk of falls are crucial for implementing effective measures to alleviate the adv
Externí odkaz:
https://doaj.org/article/9976af289f504788ad964f5e9a5d68e1
Publikováno v:
Electronics Letters, Vol 59, Iss 20, Pp n/a-n/a (2023)
Abstract Falling poses significant risks, especially for the geriatric population. In this study, the authors introduce an innovative approach to privacy‐preserving fall detection using computer vision. The authors’ technique leverages a deep neu
Externí odkaz:
https://doaj.org/article/c2dd0c89753e4152a3d925637ae31b3d
Publikováno v:
Electronics Letters (Wiley-Blackwell); Oct2023, Vol. 59 Issue 20, p1-3, 3p