Dangerous goods vehicle identification method and device, computer storage medium and electronic equipment
A vehicle identification and dangerous goods technology, applied in the field of intelligent transportation, can solve the problems of inability to achieve large-scale and timely supervision, low efficiency, high cost, etc., and achieve the effect of efficient and intelligent identification of dangerous goods vehicles
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Embodiment 1
[0028] figure 1 It shows a schematic flowchart of the implementation of the dangerous goods vehicle identification method in Embodiment 1 of the present application.
[0029] As shown in the figure, the dangerous goods vehicle identification method includes:
[0030] Step 101, acquiring road images;
[0031] Step 102, using the pre-trained multi-stage serial convolutional neural network to identify dangerous goods vehicles in the road image;
[0032] Wherein, the multi-stage serial convolutional neural network includes a first-stage convolutional neural network, a second-stage convolutional neural network, and a third-stage convolutional neural network, and the first-stage convolutional neural network recognizes the road image medium dangerous goods vehicle and its vehicle area; the second-level convolutional neural network recognizes the dangerous goods sign of the vehicle area according to the screenshot of the vehicle area returned by the first-level convolutional neural ...
Embodiment 2
[0098] Based on the same inventive concept, an embodiment of the present application provides a device for identifying dangerous goods vehicles. The principle of solving technical problems of the device is similar to that of a method for identifying dangerous goods vehicles, and the repetition will not be repeated here.
[0099] Figure 6 A schematic structural diagram of a dangerous goods vehicle identification device in Embodiment 2 of the present application is shown.
[0100] As shown in the figure, the dangerous goods vehicle identification device includes:
[0101] An acquisition module 601, configured to acquire road images;
[0102] An identification module 602, configured to identify dangerous goods vehicles in the road image using a pre-trained multi-stage serial convolutional neural network;
[0103] Wherein, the multi-stage serial convolutional neural network includes a first-stage convolutional neural network, a second-stage convolutional neural network, and a t...
Embodiment 3
[0131] Based on the same inventive concept, an embodiment of the present application further provides a computer storage medium, which will be described below.
[0132] The computer storage medium stores a computer program thereon, and when the computer program is executed by a processor, the steps of the dangerous goods vehicle identification method according to the first embodiment are realized.
[0133] Using the computer storage medium provided in the embodiment of the present application, based on the convolutional neural network, can accurately identify various dangerous goods signs on the dangerous goods vehicle body, and realize fully automatic, accurate and efficient intelligent identification of dangerous goods vehicles.
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