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没有标记的姿势估计的进步是否意味着更高质量的研究? 一个系统的审查

Shivam Bhola^1,2, Hyun-Bin Kim³, Hyeon Su Kim³

¹Department of Orthopedic Surgery, Inha University Hospitals, Incheon, Republic of Korea.

Frontiers in behavioral neuroscience

|September 8, 2025

概括

没有标记器的姿势估计有助于计算机视觉,但它在动物研究中的应用是有限的. 标准化协议对于更广泛的采用和对临床前行为更深入的了解至关重要.

科学领域:

计算机视觉计算机视觉
神经科学是一个神经科学.
行为科学行为科学

背景情况:

没有标记器的姿势估计已经彻底改变了计算机视觉.
它在科学研究中的应用,特别是动物模型,需要有系统的文档.
尽管有先进的算法,但研究中的当前使用和整合仍然不清楚.

研究的目的:

系统地审查在动物模型中的姿势估计技术的应用.
确定使用这些技术的趋势,差距和模式.
评估在科学研究中采用和整合无标记体位估计的采用率.

主要方法:

在Crossref,OpenAlex,PubMed和Scopus (2016-2025) 中进行全面的文献搜索.
从16,412个获取的条目中对1000个标题和摘要进行了人工智能辅助选.
67篇选定的论文被分类为以工具为中心,以方法为中心和以研究为中心的研究.

主要成果:

动物姿势估计研究的出版频率加速,超过一半的研究是在2021年后发表的.
确定了30篇以工具为重点,28篇以方法为重点和9篇以研究为重点的论文.
新兴趋势包括新的关键点检测方法和整合到跨疾病模型的行为实验中.

结论:

没有标记器的姿势估计技术取得了重大进展,但面临着有限的广泛应用.
传统的行为分析仍然很普遍,这表明先进工具的利用不足.
标准化协议对于弥合差距和释放这些技术在临床前行为科学中的全部潜力至关重要.

关键词:

行为分类行为分类.关键点检测检测的关键点检测没有标记器的姿势估计估计.动物模型动物模型系统性审查系统性审查

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