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- W2892862655 abstract "Dangerous goods transport vehicles can cause serious physical and environmental damage in the event of a traffic accident. It is an urgent need for the road management department to strengthen the monitoring of these vehicles. Therefore, this paper has carried out the research on the automatic vehicle mark recognition for dangerous goods. Compared with other methods, the method of target detection based on machine learning is usually able to achieve better results. Comprehensive consideration of the difficulty of training and the requirements of computer hardware, and for improving the recognition accuracy of vehicle mark, a method is proposed by adaptive improved cascade classifier. The training steps of the classifiers and the detailed target detection process are given in this paper. The results show that this method can correctly recognize the most of vehicle mark for dangerous goods by computer experiments." @default.
- W2892862655 created "2018-10-05" @default.
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- W2892862655 date "2018-05-01" @default.
- W2892862655 modified "2023-09-27" @default.
- W2892862655 title "The Research on Automatic Vehicle Mark Recognition for Dangerous Goods" @default.
- W2892862655 doi "https://doi.org/10.1109/imcec.2018.8469285" @default.
- W2892862655 hasPublicationYear "2018" @default.
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