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Author:

Wu, Peiqi (Wu, Peiqi.) | Huang, Zhangqin (Huang, Zhangqin.) (Scholars:黄樟钦) | Li, Da (Li, Da.)

Indexed by:

CPCI-S

Abstract:

In the process of Chinese license plate recognition, the main problems are as follows, such as the feature extraction method is cumbersome and inefficient, the Chinese character recognition rate is low. This paper studies the license plate technology in depth based on convolution neural network. In order to solve the problem of low recognition rate of Chinese characters, we use continuous convolution layers to convolve the image and extract more characters. Experiments show that the proposed method can more effectively extract the license plate characteristics, improve the license plate recognition rate.

Keyword:

continuous convolution license plate character recognition convolution neural network

Author Community:

  • [ 1 ] [Wu, Peiqi]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing Engn Res Ctr IoT Software & Syst, Beijing, Peoples R China
  • [ 2 ] [Huang, Zhangqin]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing Engn Res Ctr IoT Software & Syst, Beijing, Peoples R China
  • [ 3 ] [Li, Da]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing Engn Res Ctr IoT Software & Syst, Beijing, Peoples R China

Reprint Author's Address:

  • 黄樟钦

    [Huang, Zhangqin]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing Engn Res Ctr IoT Software & Syst, Beijing, Peoples R China

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Source :

PROCEEDINGS OF 2017 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATIONS (ICCC)

Year: 2017

Page: 1652-1656

Language: English

Cited Count:

WoS CC Cited Count: 2

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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