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author:

Liu, Shutang (Liu, Shutang.) [1] | Wang, Zhen (Wang, Zhen.) [2] | Wang, Chuansheng (Wang, Chuansheng.) [3] | Zheng, Junxian (Zheng, Junxian.) [4] | Zhang, Fuquan (Zhang, Fuquan.) [5]

Indexed by:

EI Scopus

Abstract:

This paper improves the image classification task based on deep learning and proposes a new font grading system to help calligraphy lovers to practice calligraphy. The basic model of the framework proposed in this paper is ResNet, and then dilated convolution, deformable convolutional, and deformable pooling are used on the traditional ResNet to improve performance. Experimental results show that the proposed algorithm can make a reasonable judgment on handwriting. © Springer Nature Singapore Pte Ltd. 2020.

Keyword:

Convolution Deep learning Deformation Grading Image enhancement Multimedia signal processing

Community:

  • [ 1 ] [Liu, Shutang]Minjiang University, Fuzhou University Town, Fuzhou; 350108, China
  • [ 2 ] [Wang, Zhen]Minjiang University, Fuzhou University Town, Fuzhou; 350108, China
  • [ 3 ] [Wang, Chuansheng]Harbin University of Science and Technology, Harbin; 150080, China
  • [ 4 ] [Zheng, Junxian]Minjiang University, Fuzhou University Town, Fuzhou; 350108, China
  • [ 5 ] [Zhang, Fuquan]Minjiang University, Fuzhou University Town, Fuzhou; 350108, China

Reprint 's Address:

  • [zhang, fuquan]minjiang university, fuzhou university town, fuzhou; 350108, china

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Source :

ISSN: 2190-3018

Year: 2020

Volume: 157

Page: 443-450

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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