The Use of Synthetic IMU Signals in the Training of Deep Learning Models Significantly Improves the Accuracy of Joint Kinematic Predictions.
Mohsen Sharifi RenaniAbigail M. EustaceCasey A. MyersChadd W. ClaryPublished in: Sensors (2021)
Keyphrases
- 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