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- W4283726273 abstract "Gait can be defined as the individuals manner of walking. Its analysis can provide significant information about their identity and health, opening a wide range of possibilities in the field medical diagnosis. In this paper we have introduced an innovated method that implement the artificial intelligence to classify human gait in video sequence. We exploited modern library based on deep learning to estimate human pose, extract the gait features and analyses videos, we have used conventional neural networks to classify normal and pathological gait. We have used Anaconda to code with Python and some packages such as Jupyter, Keras,Tensorflow, MediaPipe and DeepPose." @default.
- W4283726273 created "2022-07-01" @default.
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- W4283726273 date "2022-05-17" @default.
- W4283726273 modified "2023-09-26" @default.
- W4283726273 title "Gait Analysis and Detection of Human Pose Diseases" @default.
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- W4283726273 doi "https://doi.org/10.1109/codit55151.2022.9804057" @default.
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