TY - GEN
T1 - Recognition model based on residual networks for cursive Hanja recognition
AU - Lee, Sangwon
AU - Jang, Gil Jin
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/12
Y1 - 2017/12/12
N2 - With the development of algorithms and computer skills, deep learning using CNN (convolutional neural network) has been applied to various fields, especially in image processing field. In this paper, we designed an improved model based on ResNet with CNN structure, and learned the database. The Chaucer Database used in the experiment consisted of 824 Chinese characters among the Chinese characters registered in the Dictionary of Old Document Type Usage Dictionary of the Korean Studies Data Portal and total of 240,000 data. The experiment used 10-fold cross-validation. The ResNet-based percussive network used in the experiments showed an average of 94.7% top-1 accuracy in the post hoc classification test.
AB - With the development of algorithms and computer skills, deep learning using CNN (convolutional neural network) has been applied to various fields, especially in image processing field. In this paper, we designed an improved model based on ResNet with CNN structure, and learned the database. The Chaucer Database used in the experiment consisted of 824 Chinese characters among the Chinese characters registered in the Dictionary of Old Document Type Usage Dictionary of the Korean Studies Data Portal and total of 240,000 data. The experiment used 10-fold cross-validation. The ResNet-based percussive network used in the experiments showed an average of 94.7% top-1 accuracy in the post hoc classification test.
KW - Convolutional neural network
KW - Hanja
KW - OCR (optical character recognition)
KW - residual network
UR - http://www.scopus.com/inward/record.url?scp=85046887631&partnerID=8YFLogxK
U2 - 10.1109/ICTC.2017.8191045
DO - 10.1109/ICTC.2017.8191045
M3 - Conference contribution
AN - SCOPUS:85046887631
T3 - International Conference on Information and Communication Technology Convergence: ICT Convergence Technologies Leading the Fourth Industrial Revolution, ICTC 2017
SP - 579
EP - 583
BT - International Conference on Information and Communication Technology Convergence
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Information and Communication Technology Convergence, ICTC 2017
Y2 - 18 October 2017 through 20 October 2017
ER -