Fatigue driving behavior detection system based on parallel cross convolutional neural network
A convolutional neural network and fatigue driving technology, applied in the field of car safety driving, can solve problems such as inconvenient wearing, inconvenient practical application, and low accuracy rate, and achieve the effect of meeting real-time requirements, obvious classification effect, and small memory usage
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[0048] The present invention will be described in detail below in conjunction with various embodiments shown in the drawings. However, these embodiments do not limit the present invention, and any structural, method, or functional changes made by those skilled in the art according to these embodiments are included in the protection scope of the present invention.
[0049] Such as figure 1 As shown, the activation of driver fatigue detection is determined by the driving speed. When the driving speed exceeds 20km / h, the fatigue driving system starts to work. The camera placed in front of the driver captures the image of the driver's driving state, and takes pictures every 5s. Then call the trained convolutional neural network model to analyze the captured images, and output the judgment result of the driving state. If the driving state of the driver is in a safe state, continue to analyze the next frame of image. If the driving state of the driver is judged to be fatigued After...
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