The driver state monitoring is becoming one of the research hotspots in the field of traffic and vehicle safety, which can ensure driving safety by monitoring the driver's state. Therefore, this work makes an attempt to recognize driver's mental load and emotional states. However, the reliability and accuracy of driver status detection largely depend on the extracted features and the detection algorithm. The existing methods mainly improve accuracy by increasing the number of features, but for the problem with limited training samples, the incr...
