文化计算 |
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一种基于深度学习的古彝文识别方法 |
陈善雄1, 王小龙1, 韩旭1, 刘云2, 王明贵2 |
1.西南大学 计算机与信息科学学院,重庆 400715 2.贵州工程应用技术学院 彝文研究院,贵州 毕节 551700 |
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A recognition method of Ancient Yi character based on deep learning |
Shanxiong CHEN1, Xiaolong WANG1, Xu HAN1, Yun LIU2, Minggui WANG2 |
1.Southwest University, Chongqing 400715, China 2.Department of Information Engineering, Guizhou University of Engineering Science,Bijie 551700, Guizhou Province, China |
引用本文:
陈善雄, 王小龙, 韩旭, 刘云, 王明贵. 一种基于深度学习的古彝文识别方法[J]. 浙江大学学报(理学版), 2019, 46(3): 261-269.
Shanxiong CHEN, Xiaolong WANG, Xu HAN, Yun LIU, Minggui WANG. A recognition method of Ancient Yi character based on deep learning. Journal of Zhejiang University (Science Edition), 2019, 46(3): 261-269.
链接本文:
https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2019.03.001
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https://www.zjujournals.com/sci/CN/Y2019/V46/I3/261
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1 ZHUC X. Collection and Study of Ancient Books in Yi Language[M].Beijing:Ethnic Press,2008 2 GAOJ,LIUJ Z. Problems and countermeasures of digitization of ancient books in mainland China[J]. Journal of Chinese Library,2013,39(4):110-119. 3 WANGJ M,WENY H,LIY Q,et al. The recognition system of old-Yi character based on the image segmentation[J].Journal of Yunnan Nationalities University (Natural Science Edition),2018,17(1):76-79. 4 ZHUL H,WANGJ M. Off-line handwritten Yi character recognition based on the multi-classifier ensemble with combination features [J]. Journal of Yunnan Nationalities University (Natural Science Edition), 2010,19(5):329-333. 5 朱宗晓,吴显礼.脱机印刷体彝族文字识别系统的原理与实现[J].计算机技术与发展,2012,22(2):85-88. ZHU Z X,WU X L. Principle and implementation of an off-line printed Yi character recognition system[J].Computer Technology and Development,2012,22(2):85-88.doi:10.3969/j.issn.1673-629X.2012.02.022 6 LIUS,LIY D. Design and realization on character segmentation method for Yi language[J]. Journal of South-Central University for Nationalities(Natural Science Edition),2007,26(3):74-76. 7 WUB. Analysis and research of standard Yi characters based on the angel of character recognition[J].Journal of Southwest Minzu University(Humanities and Social Science Edition),2018(9):47-53. 8 Yi Literature Cooperation Group.Collection of Yi Chracters[M]. Kunming:Yunnan Nationalities Press,2004. 9 RENX H, ZHOUY, HEJ H, et al. A convolutional neural network-based Chinese text detection algorithm via text structure modeling[J]. IEEE Transactions on Multimedia, 2017,19(3):506-518.doi:10.1109/tmm.2016.2625259 10 AKHANDM A H, AHMEDM, RAHMANM M H,et al. Convolutional neural network training incorporating rotation-based generated patterns and handwritten numeral recognition of major Indian scripts[J]. IETE Journal of Research, 2018,64(2):176-194.doi:10.1080/03772063.2017.1351322 11 NASEEA, ZAFARK. Comparative analysis of raw images and meta feature based Urdu OCR using CNN and LSTM[J]. International Journal of Advanced Computer Science and Applications,2018,9(1):419-424.doi:10.14569/ijacsa.2018.090157 12 SINDAGIV A, PATELV M. A survey of recent advances in CNN-based single image crowd counting and density estimation[J].Pattern Recognition Letters,2018,107:3-16doi:10.1016/j.patrec.2017.07.007 13 DENGX M, ZHANGY D,YANGS, et al. Joint hand detection and rotation estimation using CNN[J].IEEE Transactions on Image Processing, 2018,27(4):1888-1900.doi:10.1109/tip.2017.2779600 14 CICHOCKIA, AMARIS I. Families of Alpha-Beta-and Gamma- divergences: Flexible and robust measures of similarities[J]. Entropy, 2010,12(6):1532-1568. 15 CICHOCKIA, CRUCESS, AMARIS. Generalized Alpha-Beta divergences and their application to robust nonnegative matrix factorization[J].Entropy, 2011,13(1):134-170.doi:10.3390/e13010134 16 SHIW W, GONGY H, TAOX Y,et al. Training DCNN by combining max-margin, max-correlation objectives, and correntropy loss for multilabel image classification[J].IEEE Transactions on Neural Networks and Learning Systems,2017,29(7):2896-2908.doi:10.1109/tnnls.2017.2705222 17 SENGUPTAA , SHIMY, ROY K. Proposal for an all-spin artificial neural network: Emulating neural and synaptic functionalities through domain wall motion in ferromagnets[J].IEEE Transactions on Biomedical Circuits and Systems, 2016,10(6):1152-1160.doi:10.1109/tbcas.2016.2525823 18 KNAGP, KIM J K, CHENT, et al. A sparse coding neural network ASIC with on-chip learning for feature extraction and encoding[J]. IEEE Journal of Solid-State Circuits, 2015,50(4):1070-1079.doi:10.1109/jssc.2014.2386892 19 QIANS,LIUH,LIUC,et al. Adaptive activation functions in convolutional neural networks[J]. Neurocomputing, 2018,272:204-212.doi:10.1016/j.neucom.2017.06.070 20 áARCOS-GARCíA, álVAREZ-GARCíAJ A, SORIA-MORILLOL M. Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods[J]. Neural Networks, 2018,99:158-165.doi:10.1016/j.neunet.2018.01.005 21 GOPALAKRISHNANK, KHAITANS K, CHOUDHARYA, et al. Deep convolutional neural networks with transfer learning for computer vision-based data-driven pavement distress detection[J]. Construction and Building Materials, 2017,157:322-330.doi:10.1016/j.conbuildmat.2017.09.110 22 Guizhou Institute of Yi Studies. Southwest Yi Chi[M].Guiyang: Guizhou Nationalities Press,2015. |
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