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- W2379733962 abstract "the paper aims to recognizing vehicles' license plates characters via analysis of intelligent algorithms deployed on recognition of vehicles' license plates.The method of recognizing rough grid features based on neural network are proposed,after literature review and comparison of generally used recognition method on vehicles' license plates.In this method,character images are pre-processed at the beginning,then the improved rough grid features are extracted from the original images,and finally the extracted features were used to train the neural network.All the characters used in the case study,such as Chinese characters,capital English letter,number are extracted from real image.The artificially extracted Chinese characters can cover the mostly used Chinese characters on vehicles' license plates and the extracted English letter and number totally match the real situation.The recognition rate on number and letter are very high.The recognition rate on number is 99.16%.The results show that the proposed rough grid features recognition method is feasible and effective." @default.
- W2379733962 created "2016-06-24" @default.
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- W2379733962 date "2007-01-01" @default.
- W2379733962 modified "2023-09-25" @default.
- W2379733962 title "The Recognition of Vehicles' License Plates Characters Based on Rough Grid Neural Network" @default.
- W2379733962 hasPublicationYear "2007" @default.
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