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Driver fatigue and inattention have long been recognised as the main contributing factors in traffic accidents. This study presents a novel system which applies convolutional neural network (CNN) to automatically learn and predict pre-defined driving postures. The main idea is to monitor driver hand position with discriminative information extracted to predict safe/unsafe driving posture. In comparison...
Gait as a biometric feature that can be measured remotely without physical contact and proximal sensing has attract significant attention. This paper proposes to use con-volutional neural networks (ConvNets) and multi-task learning model(MLT) to identify human gait and to predict multiple human attributes simultaneously. In comparison to previous approaches, two novelty in our convolutional approach...
Driver inattention has long been recognized as the main contributing factors in traffic accidents. Development of intelligent driver assistance systems with embedded functionality of driver vigilance monitoring is therefore an urgent and challenging task. This paper presents a novel system which applies convolutional neural network to automatically learn and predict the state of driver's eye, mouth...
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