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Procedia Computer Science
Article . 2019 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Procedia Computer Science
Article
License: CC BY NC ND
Data sources: UnpayWall
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Document images classification based on deep learning

Authors: Biao Hu; Daji Ergu; Huan Yang; Kuiyi Liu; Ying Cai 0002;

Document images classification based on deep learning

Abstract

Abstract 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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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
gold