[1]陈蕊丽. 浅谈伪造印章的犯罪特点及防伪措施[J]. 中国防伪, 2004(11):9-12.
[2]孙法国. 常见印章制作的方法及伪造印章的检验鉴定[J]. 探索科学, 2019(3):237.
[3]许爱东. 印章印文鉴定理论与实务研究[M]. 北京:法律出版社, 2015.
[4]刘丰威,潘炜,韩丽丽. 稽查中印章真伪识别智能算法[J]. 中国高新科技, 2020(13):130-131.
[5]MATSUURA T, YAMAZAKI K. A robust seal imprint verification method with rotation invariance[C]// 2005 13th European Signal Processing Conference. IEEE, 2013. DOI: 10.5281/zenodo.39165.
[6]耿建玲,陈纯,陈耀武,等. 基于小波多尺度分解的印鉴图像配准[J]. 计算机工程与应用, 2006,42(1):34-36.
[7]梅天灿,秦前清,钟永正. 基于自适应特征提取的印鉴自动识别方法[J]. 计算机工程与应用, 2004,40(24):54-56.
[8]张先萌,罗安玉,王翔,等. 用矩不变量实现印鉴自动识别[J]. 电子学报, 1995,23(4):100-103.
[9]胡庆,杨静宇,张黔,等. 基于知识的印鉴鉴别方法[J]. 自动化学报, 1991,17(6):696-704.
[10]高文,董胜富,周世意. 基于边缘匹配的印鉴自动鉴别方法[J]. 模式识别与人工智能, 1994,7(4):338-342.
[11]SUN B, HUA S J, LI S T, et al. Graph-matching-based character recognition for Chinese seal images[J]. Science China(Information Sciences), 2019,62(9):37-50.
[12]DAI T T, SUN B. Novel features for character extraction of historical Chinese seal images[J]. Sensing and Imaging, 2019,20. DOI: 10.1007/s11220-019-0253-z.
[13]杨德胜. 基于AIoT的智慧印章管控系统探索与实践[J]. 电力信息与通信技术, 2021,19(7):98-103.
[14]宋禹廷. 基于机器视觉的印章识别系统设计与实现[D]. 成都:电子科技大学, 2020.
[15]张倩,郝红光,韩星周. 利用VGGnet对印章印文分类识别的适用条件研究[J]. 通信技术, 2019,52(7):1639-1642.
[16]HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning for image recognition[C]// 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2016:770-778.
[17]SARANGAPANI J. Neural engineering: Computation, representation, and dynamics in neurobiological systems [book review][J]. IEEE Control Systems Magazine, 2005,25(6):102-106.
[18]赵志成,罗泽,王鹏彦,等. 基于深度残差网络图像分类算法研究综述[J]. 计算机系统应用, 2020,29(1):14-21.
[19]刘敦强,沈峘,夏瀚笙,等. 一种基于深度残差网络的车型识别方法[J]. 计算机技术与发展, 2018,28(5):42-46.
[20]SZEGEDY C, IOFFE S, VANHOUCKE V, et al. Inception-v4, Inception-ResNet and the impact of residual connections on learning[C]// Proceedings of the 31st AAAI Conference on Artificial Intelligence. 2017:4278-4284.
[21]ROY P P, PAL U, LLADS J. Seal detection and recognition[C]// IEEE 2009 10th International Conference on Document Analysis and Recognition. 2009:101-105.
[22]王圣江. 露白特征在印章印文检验中的应用价值研究[J]. 中国公共安全(学术版), 2020(1):133-137.
[23]MELEKHOV I, KANNALA J, RAHTU E. Siamese network features for image matching[C]// 2016 23rd International Conference on Pattern Recognition (ICPR). IEEE, 2016. DOI: 10.1109/ICPR.2016.7899663.
[24]CHOPRA S, HADSELL R, LECUN Y. Learning a similarity metric discriminatively, with application to face verification[C]// 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05). IEEE, 2005:539-546.
[25]WANG Z Y, LIAN J, SONG C F, et al. CSRS: A Chinese seal recognition system with multi-task learning and automatic background generation[J]. IEEE Access, 2019,7:96628-96638.
[26]AHRABIAN K, BABAALI B. Usage of autoencoders and siamese networks for online handwritten signature verification[J]. Neural Computing and Applications, 2019,31:9321-9334.
[27]翟惠林. 带有防伪芯片的物理印章信息管理系统的研究与实现[D]. 杭州:浙江工业大学, 2013.
[28]刘润杰,龙华秋,容振邦. 基于RESTful架构的任务发放平台开发[J]. 网络安全技术与应用, 2019(9):41-43.
[29]杜英魁,王杨 关屏,等. 基于Spring Boot的云端数据监控管理与可视化应用系统[J]. 计算机系统应用, 2020,29(5):125-129.
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