Document images classification based on deep learning | Zendy

Biao Hu | Zendy; Daji Ergu | Zendy; Huan Yang | Zendy; Kuiyi Liu | Zendy; Ying Cai | Zendy

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Document images classification based on deep learning

Author(s) -

Biao Hu,

Daji Ergu,

Huan Yang,

Kuiyi Liu,

Ying Cai

Publication year - 2019

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2019.12.018

Subject(s) - softmax function , computer science , artificial intelligence , image (mathematics) , contextual image classification , pattern recognition (psychology) , workflow , convolution (computer science) , deep learning , artificial neural network , database

In the financial business, there are cumbersome and error-prone manual procedures and long workflows. In this paper, MSCNN model is proposed to solve automatically identify and classify images such as documents. First, the image data is preprocessed to enhance the image features. Then, the image is extracted by the cross-connect structure and multi-channel convolution. Finally, the image is classified by softmax layer. The experimental results on the dataset show that the proposed model has a high classification accuracy in image classification.

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