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Tytuł pozycji:

Feature Extraction of Ancient Chinese Characters Based on Deep Convolution Neural Network and Big Data Analysis.

Tytuł:
Feature Extraction of Ancient Chinese Characters Based on Deep Convolution Neural Network and Big Data Analysis.
Autorzy:
Zhang C; College of Literature and Journalism, Chengdu University, Chengdu 610106, Sichuan, China.
Liu X; School of Humanities and Communication, Sanya University, Sanya 572022, Hainan, China.
Źródło:
Computational intelligence and neuroscience [Comput Intell Neurosci] 2021 Aug 30; Vol. 2021, pp. 2491116. Date of Electronic Publication: 2021 Aug 30 (Print Publication: 2021).
Typ publikacji:
Journal Article; Retracted Publication
Język:
English
Imprint Name(s):
Original Publication: New York, NY : Hindawi Pub. Corp.
MeSH Terms:
Big Data*
Data Analysis*
Algorithms ; China ; Neural Networks, Computer
References:
Sensors (Basel). 2021 Apr 18;21(8):. (PMID: 33919618)
Multimed Syst. 2021 Apr 28;:1-10. (PMID: 33935377)
Entry Date(s):
Date Created: 20210910 Date Completed: 20210913 Latest Revision: 20230811
Update Code:
20240105
PubMed Central ID:
PMC8423538
DOI:
10.1155/2021/2491116
PMID:
34504520
Czasopismo naukowe
In recent years, deep learning has made good progress and has been applied to face recognition, video monitoring, image processing, and other fields. In this big data background, deep convolution neural network has also received more and more attention. In order to extract the ancient Chinese characters effectively, the paper will discuss the structure model, pool process, and network training of deep convolution neural network and compare the algorithm with the traditional machine learning algorithm. The results show that the accuracy and recall rate of the Chinese characters in the plaque of Ming Dynasty can reach the peak, 81.38% and 81.31%, respectively. When the number of training samples increases to 50, the recognition rate of MFA is 99.72%, which is much higher than other algorithms. This shows that the algorithm based on deep convolution neural network and big data analysis has excellent performance and can effectively identify the Chinese characters under different dynasties, different sample sizes, and different interference factors, which can provide a powerful reference for the extraction of ancient Chinese characters.
Competing Interests: The authors declare that they have no conflicts of interest or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2021 Cheng Zhang and Xingjun Liu.)
Retraction in: Comput Intell Neurosci. 2023 Aug 2;2023:9801976. (PMID: 37564603)
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