A Bioinspired Feature-Projection-Based Approach to Electromyographic Pattern Recognition Based for High Dimensional Sparse Sensor Data.
Giovanni SchiboniPeidong LiangChenguang YangLiming ChenSanja DogramadziPublished in: UIC/ATC/ScalCom (2015)
Keyphrases
- sensor data
- high dimensional
- pattern recognition
- sensor networks
- sparse data
- dimensionality reduction
- sensor measurements
- low dimensional
- data streams
- high dimensional data
- image processing
- health monitoring
- sparse coding
- computer vision
- additive models
- neural network
- multiple sensors
- earth observation
- image analysis
- feature space
- smart environments
- high dimension
- sensor readings
- heterogeneous sensor networks
- biologically inspired
- human activities
- sparse representation
- physical objects
- stream data
- multispectral
- raw sensor data
- feature extraction