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The Use of Synthetic IMU Signals in the Training of Deep Learning Models Significantly Improves the Accuracy of Joint Kinematic Predictions.
Mohsen Sharifi Renani
Abigail M. Eustace
Casey A. Myers
Chadd W. Clary
Published in:
Sensors (2021)
Keyphrases
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learning models
significantly improves the accuracy
machine learning
learning algorithm
loss function
learning problems
supervised learning
learning tasks
machine learning algorithms
classification models
semi supervised learning
conditional random fields
degrees of freedom
sparse metric learning
machine learning models
inverse kinematics
real world
active learning
artificial neural networks
training set
computer vision
joint angles
genetic algorithm
data sets