一种基于深度学习的青铜器铭文识别方法

李文英; 曹斌; 曹春水; 黄永祯; 李文英; 曹斌; 曹春水; 黄永祯

doi:10.16383/j.aas.2018.c180152

[1]

马承源.中国古代青铜器.第2版.上海:上海人民出版社, 2016. 9-41

Ma Cheng-Yuan. Ancient Chinese Bronzes (Second Edition). Shanghai:Shanghai Renmin Press, 2016. 9-41

[2]

李学勤.古文字学初阶.第2版.北京: 中华书局, 2006. 9-46

Li Xue-Qin. Primary Chinese Paleography (Second Edition). Beijing: Zhonghua Book Company, 2006. 9-46

[3]

高明.中国古文字学通论.北京:北京大学出版社, 1996. 56-170

Gao Ming. General Theory of Chinese Paleography. Beijing:Beijing University Press, 1996. 56-170

[4]

高明, 涂白奎.古文字类编.上海:上海古籍出版社, 2014. 1-1427

Gao Ming, Tu Bai-Kui. Ancient Chinese Character Type Series. Shanghai:Shanghai Classics Publishing House, 2014. 1-1427

[5]

张亚初.殷周金文集成引得.北京: 中华书局, 2001. 1-225

Zhang Ya-Chu. Shang and Zhou Dynasties Bronze Inscriptions Integration Index. Beijing: Zhonghua Book Company, 2001. 1-225

[6]

周新伦, 李锋, 华星城, 韦剑.甲骨文计算机识别方法研究.复旦学报(自然科学版), 1996, 35(5):481-486 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199600072768

Zhou Xin-Lun, Li Feng, Hua Xing-Cheng, Wei Jian. A method of Jia Gu Wen recognition based on a two-level classification. Journal of Fudan University (Natural Science), 1996, 35(5):481-486 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199600072768

[7]

李峰, 周新伦.甲骨文自动识别的图论方法.电子科学学刊, 1996, 18(S1):41-47 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199600067408

Li Feng, Zhou Xin-Lun. Recohnition of Jia Gu Wen based on graph theory. Journal of Electronics & Information Technology, 1996, 18(S1):41-47 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199600067408

[8]

顾绍通.基于拓扑配准的甲骨文字形识别方法.计算机与数字工程, 2016, 44(10):2001-2006 doi: 10.3969/j.issn.1672-9722.2016.10.029

Gu Shao-Tong. Identification of oracle-bone script fonts based on topological registration. Computer & Digital Engineering, 2016, 44(10):2001-2006 doi: 10.3969/j.issn.1672-9722.2016.10.029

[9]

吕肖庆, 李沫楠, 蔡凯伟, 王晓, 唐英敏.一种基于图形识别的甲骨文分类方法.北京信息科技大学学报, 2010, 25(S2):92-96 http://d.old.wanfangdata.com.cn/Conference/7452730

Lv Xiao-Qing, Li Mo-Nan, Cai Kai-Wei, Wang Xiao, Tang Ying-Min. A graphic-based method for Chinese oracle-bone classification. Journal of Beijing Information Science & Technology University, 2010, 25(S2):92-96 http://d.old.wanfangdata.com.cn/Conference/7452730

[10]

王嘉梅, 文永华, 李燕青, 高雅莉.基于图像分割的古彝文字识别系统研究.云南民族大学学报(自然科学版), 2008, 17(1):76-79 doi: 10.3969/j.issn.1672-8513.2008.01.019

Wang Jia-Mei, Wen Yong-Hua, Li Yan-Qing, Gao Ya-Li. The recognition system of old-Yi character based on the image segmentation. Journal of Yunnan Nationalities University (Natural Sciences Edition), 2008, 17(1):76-79 doi: 10.3969/j.issn.1672-8513.2008.01.019

[11]

孙华.基于多特征融合SVM的古汉字图像识别研究[硕士学位论文], 中南大学, 中国, 2010 http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y1721380

Sun Hua. Study of Ancient Chinese Character based on Multi-feature SVM Image Recognition Method[Master thesis], Central South University, China, 2010 http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y1721380

[12]

孙莹莹.基于混合核LS-SVM的古汉字图像识别[硕士学位论文], 安徽大学, 中国, 2015 http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y2805808

Sun Ying-Ying. Recognition of Ancient Chinese Characters Based on Hybrid Kernel LS-SVM[Master thesis], Anhui University, China, 2015 http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y2805808

[13]

Krizhevsky K, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks. In: Proceedings of the 25th International Conference on Neural Information Processing Systems. Lake Tahoe, USA: ACM, 2012. 1097-1105

[14]

Deng J, Dong W, Socher R, Li L J, Li K, Li F F. ImageNet: a large-scale hierarchical image database. In: Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition. Miami, USA: IEEE, 2009. 248-255

[15]

Cao C S, Liu X M, Yang Y, Yu Y N, Wang J, Wang Z L, et al. Look and think twice: capturing top-down visual attention with feedback convolutional neural networks. In: Proceedings of the 2015 IEEE International Conference on Computer Vision. Santiago, Chile: IEEE, 2015. 2956-2964

[16]

Zhang X Y, Bengio Y, Liu C L. Online and offline handwritten Chinese character recognition:a comprehensive study and new benchmark. Pattern Recognition, 2017, 61:348-360 doi: 10.1016/j.patcog.2016.08.005

[17]

Wu Y C, Yin F, Liu C L. Improving handwritten Chinese text recognition using neural network language models and convolutional neural network shape models. Pattern Recognition, 2017, 65:251-264 doi: 10.1016/j.patcog.2016.12.026

[18]

Zeiler M D, Fergus R. Visualizing and understanding convolutional networks. In: Proceedings of the 13th European Conference on Computer Vision. Zurich, Switzerland: Springer, 2014. 818-833

[19]

Zhou B L, Khosla A, Lapedriza A, Oliva A, Torralba A. Object detectors emerge in deep scene CNNs. In: Proceedings of the 2015 International Conference on Learning Representations. San Diego, USA: ICLR, 2015.

[20]

Simonyan K, Zisserman A. Very deep convolutional networks for large-Scale image recognition. In: Proceedings of the 2015 International Conference on Learning Representations. San Diego, USA: ICLR, 2015.

[21]

Szegedy C, Liu W, Jia Y Q, Sermanet P, Reed S, Anguelov D, et al. Going deeper with convolutions. In: Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition. Boston, USA: IEEE, 2015. 1-9

[22]

He K M, Zhang X Y, Ren S Q, Sun J. Deep residual learning for image recognition. In: Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, USA: IEEE, 2016. 770-778

[23]

Mnih V, Heess N, Graves A, Kavukcuoglu K. Recurrent models of visual attention. In: Proceedings of the 27th International Conference on Neural Information Processing Systems. Montreal, Canada: ACM, 2014. 2204-2212

[1]	马承源.中国古代青铜器.第2版.上海:上海人民出版社, 2016. 9-41 Ma Cheng-Yuan. Ancient Chinese Bronzes (Second Edition). Shanghai:Shanghai Renmin Press, 2016. 9-41
[2]	李学勤.古文字学初阶.第2版.北京: 中华书局, 2006. 9-46 Li Xue-Qin. Primary Chinese Paleography (Second Edition). Beijing: Zhonghua Book Company, 2006. 9-46
[3]	高明.中国古文字学通论.北京:北京大学出版社, 1996. 56-170 Gao Ming. General Theory of Chinese Paleography. Beijing:Beijing University Press, 1996. 56-170
[4]	高明, 涂白奎.古文字类编.上海:上海古籍出版社, 2014. 1-1427 Gao Ming, Tu Bai-Kui. Ancient Chinese Character Type Series. Shanghai:Shanghai Classics Publishing House, 2014. 1-1427
[5]	张亚初.殷周金文集成引得.北京: 中华书局, 2001. 1-225 Zhang Ya-Chu. Shang and Zhou Dynasties Bronze Inscriptions Integration Index. Beijing: Zhonghua Book Company, 2001. 1-225
[6]	周新伦, 李锋, 华星城, 韦剑.甲骨文计算机识别方法研究.复旦学报(自然科学版), 1996, 35(5):481-486 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199600072768 Zhou Xin-Lun, Li Feng, Hua Xing-Cheng, Wei Jian. A method of Jia Gu Wen recognition based on a two-level classification. Journal of Fudan University (Natural Science), 1996, 35(5):481-486 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199600072768
[7]	李峰, 周新伦.甲骨文自动识别的图论方法.电子科学学刊, 1996, 18(S1):41-47 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199600067408 Li Feng, Zhou Xin-Lun. Recohnition of Jia Gu Wen based on graph theory. Journal of Electronics & Information Technology, 1996, 18(S1):41-47 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199600067408
[8]	顾绍通.基于拓扑配准的甲骨文字形识别方法.计算机与数字工程, 2016, 44(10):2001-2006 doi: 10.3969/j.issn.1672-9722.2016.10.029 Gu Shao-Tong. Identification of oracle-bone script fonts based on topological registration. Computer & Digital Engineering, 2016, 44(10):2001-2006 doi: 10.3969/j.issn.1672-9722.2016.10.029
[9]	吕肖庆, 李沫楠, 蔡凯伟, 王晓, 唐英敏.一种基于图形识别的甲骨文分类方法.北京信息科技大学学报, 2010, 25(S2):92-96 http://d.old.wanfangdata.com.cn/Conference/7452730 Lv Xiao-Qing, Li Mo-Nan, Cai Kai-Wei, Wang Xiao, Tang Ying-Min. A graphic-based method for Chinese oracle-bone classification. Journal of Beijing Information Science & Technology University, 2010, 25(S2):92-96 http://d.old.wanfangdata.com.cn/Conference/7452730
[10]	王嘉梅, 文永华, 李燕青, 高雅莉.基于图像分割的古彝文字识别系统研究.云南民族大学学报(自然科学版), 2008, 17(1):76-79 doi: 10.3969/j.issn.1672-8513.2008.01.019 Wang Jia-Mei, Wen Yong-Hua, Li Yan-Qing, Gao Ya-Li. The recognition system of old-Yi character based on the image segmentation. Journal of Yunnan Nationalities University (Natural Sciences Edition), 2008, 17(1):76-79 doi: 10.3969/j.issn.1672-8513.2008.01.019
[11]	孙华.基于多特征融合SVM的古汉字图像识别研究[硕士学位论文], 中南大学, 中国, 2010 http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y1721380 Sun Hua. Study of Ancient Chinese Character based on Multi-feature SVM Image Recognition Method[Master thesis], Central South University, China, 2010 http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y1721380
[12]	孙莹莹.基于混合核LS-SVM的古汉字图像识别[硕士学位论文], 安徽大学, 中国, 2015 http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y2805808 Sun Ying-Ying. Recognition of Ancient Chinese Characters Based on Hybrid Kernel LS-SVM[Master thesis], Anhui University, China, 2015 http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y2805808
[13]	Krizhevsky K, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks. In: Proceedings of the 25th International Conference on Neural Information Processing Systems. Lake Tahoe, USA: ACM, 2012. 1097-1105
[14]	Deng J, Dong W, Socher R, Li L J, Li K, Li F F. ImageNet: a large-scale hierarchical image database. In: Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition. Miami, USA: IEEE, 2009. 248-255
[15]	Cao C S, Liu X M, Yang Y, Yu Y N, Wang J, Wang Z L, et al. Look and think twice: capturing top-down visual attention with feedback convolutional neural networks. In: Proceedings of the 2015 IEEE International Conference on Computer Vision. Santiago, Chile: IEEE, 2015. 2956-2964
[16]	Zhang X Y, Bengio Y, Liu C L. Online and offline handwritten Chinese character recognition:a comprehensive study and new benchmark. Pattern Recognition, 2017, 61:348-360 doi: 10.1016/j.patcog.2016.08.005
[17]	Wu Y C, Yin F, Liu C L. Improving handwritten Chinese text recognition using neural network language models and convolutional neural network shape models. Pattern Recognition, 2017, 65:251-264 doi: 10.1016/j.patcog.2016.12.026
[18]	Zeiler M D, Fergus R. Visualizing and understanding convolutional networks. In: Proceedings of the 13th European Conference on Computer Vision. Zurich, Switzerland: Springer, 2014. 818-833
[19]	Zhou B L, Khosla A, Lapedriza A, Oliva A, Torralba A. Object detectors emerge in deep scene CNNs. In: Proceedings of the 2015 International Conference on Learning Representations. San Diego, USA: ICLR, 2015.
[20]	Simonyan K, Zisserman A. Very deep convolutional networks for large-Scale image recognition. In: Proceedings of the 2015 International Conference on Learning Representations. San Diego, USA: ICLR, 2015.
[21]	Szegedy C, Liu W, Jia Y Q, Sermanet P, Reed S, Anguelov D, et al. Going deeper with convolutions. In: Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition. Boston, USA: IEEE, 2015. 1-9
[22]	He K M, Zhang X Y, Ren S Q, Sun J. Deep residual learning for image recognition. In: Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, USA: IEEE, 2016. 770-778
[23]	Mnih V, Heess N, Graves A, Kavukcuoglu K. Recurrent models of visual attention. In: Proceedings of the 27th International Conference on Neural Information Processing Systems. Montreal, Canada: ACM, 2014. 2204-2212