基于深度学习的无标记跟踪临床记录视频中的远端解剖标志,用于评估与神经发育状态相关的婴儿运动模式

IF 2.1 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES
Hamid Abbasi, Sarah R. Mollet, Sian A. Williams, Malcolm R. Battin, Thor F. Besier, Angus J. C. McMorland
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引用次数: 0

摘要

本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep-learning-based markerless tracking of distal anatomical landmarks in clinically recorded videos for assessing infant movement patterns associated with neurodevelopmental status
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来源期刊
Journal of the Royal Society of New Zealand
Journal of the Royal Society of New Zealand 综合性期刊-综合性期刊
CiteScore
4.60
自引率
0.00%
发文量
74
审稿时长
3 months
期刊介绍: Aims: The Journal of the Royal Society of New Zealand reflects the role of Royal Society Te Aparangi in fostering research and debate across natural sciences, social sciences, and the humanities in New Zealand/Aotearoa and the surrounding Pacific. Research published in Journal of the Royal Society of New Zealand advances scientific knowledge, informs government policy, public awareness and broader society, and is read by researchers worldwide.
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