Figure 2.

Design of the automatic classification pipeline. (a) The convolutional neural network (CNN) architecture used in the study as the main classifier. The role of the sensor module is to perform sensor-specific feature extraction, the sensor fusion module fuses sensor-level features into frame-level features, and the time series modeling module captures the temporal dependencies across frame-level features. (b) Block diagram for the iterative annotation refinement (IAR) procedure used to improve CNN performance through classifier-assisted resolution of inter-annotator inconsistencies on the training data.