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摘要:
With the development of the economy and the surge in car ownership, the sale of used cars has been welcomed by more and more people, and the information of the vehicle condition is the focus information of them. The frame number is a unique number used in the vehicle, and by identifying it can quickly find out the vehicle models and manufacturers. The traditional character recognition method has the problem of complex feature extraction, and the convolutional neural network has unique advantages in processing two-dimensional images. This paper analyzed the key techniques of convolutional neural networks compared with traditional neural networks, and proposed improved methods for key technologies, thus increasing the recognition of characters and applying them to the recognition of frame number characters.
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篇名 Optimization of Convolutional Neural Network for Recognition of Vehicle Frame Number
来源期刊 电脑和通信(英文) 学科 工学
关键词 FRAME NUMBER RECOGNITION Convolutional NEURAL Network (CNN) FEATURE Extraction Pooling
年,卷(期) 2018,(11) 所属期刊栏目
研究方向 页码范围 209-215
页数 7页 分类号 TP39
字数 语种
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研究主题发展历程
节点文献
FRAME
NUMBER
RECOGNITION
Convolutional
NEURAL
Network
(CNN)
FEATURE
Extraction
Pooling
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研究去脉
引文网络交叉学科
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期刊影响力
电脑和通信(英文)
月刊
2327-5219
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
783
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0
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