An Advanced Deep Framework for Recognition of Distracted Driving Behaviors

This paper introduces a trainable deep framework called DedistractedNet for recognizing the distracted driving behaviors from an image. In contrast to other conventional strategies that use physiological sensors or on-board diagnostics, the DedistractedNet directly profiles the features of driving behaviors in the image based on the deep convolutional neural networks. Experiment results manifest that the DedistractedNet achieves superior accuracy than those of other baseline CNN methods.