Violation snapshot image AI recognition system
A recognition system and image technology, applied in character and pattern recognition, instruments, biological neural network models, etc., can solve problems such as heavy workload and difficulty in accurate review, and achieve the effect of avoiding recognition congestion, facilitating recognition, and improving verification speed.
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Embodiment 1
[0025] see Figure 1-4 , the present invention provides the following technical solutions: an AI recognition system for snapping images against regulations, comprising an image input module 1 to be identified, an image preprocessing module 4 connected to the output of the image input module 1 to be identified, and an output end of the image preprocessing module 4 Connected with neural network model module 6, the input end of neural network model module 6 is connected with neural network model building module 5, and the output end of neural network model module 6 is connected with identification result output module 7;
[0026] The neural network model module 6 includes an image distribution module 61 and several neural network model recognition modules 62, the input end of the image distribution module 61 is connected with the image preprocessing module 4, and the output end of the image distribution module 61 is connected with several neural network model recognition modules. ...
Embodiment 2
[0035] The difference of this embodiment compared with embodiment 1 is:
[0036]Concrete, the output end of several neural network model identification modules 62 is connected with illegal image storehouse 2, and the input end and output end of image input module 1 to be identified are connected with image coincidence degree comparison module 3, and image coincidence degree contrast module 3 The input end and the output end are connected with the illegal image storage library 2, and the output end of the image coincidence degree comparison module 3 is connected with the identification result output module 7.
[0037] The working principle of this embodiment: before the identification by the neural network model module 6, the image to be recognized input module 1 inputs the image to be recognized into the image coincidence degree comparison module 3, and the image coincidence degree comparison module 3 compares the image to be recognized with the The images in the violation ima...
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