Abnormal Infant Movements Classification With Deep Learning on Pose-Based Features

Abnormal Infant Movements Classification With Deep Learning on Pose-Based Features

The pursuit of early diagnosis of cerebral palsy has been an active research area with some very promising results using tools such as the General Movements Assessment (GMA). In our previous work, we explored the feasibility of extracting pose-based features from video sequences to automatically cla...

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Bibliographic Details
Main Authors: Kevin D. McCay, Edmond S. L. Ho, Hubert P. H. Shum, Gerhard Fehringer, Claire Marcroft, Nicholas D. Embleton
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Deep learning
feature extraction
classification
infants
pose-based features
Online Access:https://ieeexplore.ieee.org/document/9034058/

Internet

https://ieeexplore.ieee.org/document/9034058/

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