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Xiaohu Liu

Biographic Data

ID7791101
NAMEXiaohu Liu
GIVEN NAMESXiaohu
FAMILY NAMELiu
SIGNATURELIU X
AFFILIATIONSKunming Institute of Zoology
ORCID0000-0001-9446-7426
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS1
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2013
LATEST PUBLICATION YEAR2026
H-INDEX1
  • Predicting physical activity types in children aged 3–6 from video data using computer vision

    Open Access•Xinxin Ma, Guanggao Zhao et al.•ARTICLE•BMC Public Health•2026

    Assessing the types of physical activity (PA) in young children is crucial for exploring their relationship with health. Although existing machine learning methods have made certain progress, there are still deficiencies in non-contact, real-time dynamic monitoring and recognition accuracy. This study aims to utilize computer vision technology to construct non-contact, real-time dynamic, and high-precision recognition models for the types of phys…

  • Niche Divergence Among Sex and Age Classes in Black-and-White Snub-nosed Monkeys (Rhinopithecus bieti)

    Open Access•Yi Wan, Rui-Chang Quan et al.•ARTICLE•International Journal of…•2013•Cited by: 1•References: 32

  • Niche Divergence Among Sex and Age Classes in Black-and-White Snub-nosed Monkeys (Rhinopithecus bieti)

    Open Access•Yi Wan, Rui-Chang Quan et al.•ARTICLE•International Journal of…•2013•Cited by: 1•References: 32

  • Niche Divergence Among Sex and Age Classes in Black-and-White Snub-nosed Monkeys (Rhinopithecus bieti)

    Open Access•Yi Wan, Rui-Chang Quan et al.•ARTICLE•International Journal of…•2013•Cited by: 1•References: 32

  • Predicting physical activity types in children aged 3–6 from video data using computer vision

    Open Access•Xinxin Ma, Guanggao Zhao et al.•ARTICLE•BMC Public Health•2026

    Assessing the types of physical activity (PA) in young children is crucial for exploring their relationship with health. Although existing machine learning methods have made certain progress, there are still deficiencies in non-contact, real-time dynamic monitoring and recognition accuracy. This study aims to utilize computer vision technology to construct non-contact, real-time dynamic, and high-precision recognition models for the types of phys…

Activities of daily living (1 work) · Age groups (1 work) · Animal Behavior and Reproduction (1 work) · Animal ecology (1 work) · Animal Vocal Communication and Behavior (1 work) · Biology (1 work) · Biostatistics (1 work) · Cognitive neuroscience of visual object recognition (1 work) · Construct (python library (1 work) · Context-Aware Activity Recognition Systems (1 work)

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