“第二十一章 车牌识别”版本间的差异

来自cslt Wiki
跳转至: 导航搜索
演示链接
 
第25行: 第25行:
 
* 薪火科技[https://www.xinhuokj.com/ocr.html]
 
* 薪火科技[https://www.xinhuokj.com/ocr.html]
 
* DTK车牌识别在线演示[https://www.dtksoft.com/lprdemo]
 
* DTK车牌识别在线演示[https://www.dtksoft.com/lprdemo]
* Tanar Automatic Number Plate Reader System [https://saymannet.com/LPR-License-Plate-Recognition]
 
 
  
 
==开发者资源==
 
==开发者资源==

2023年8月13日 (日) 01:54的最后版本


教学资料

  • 教学参考
  • 课件
  • 小清爱提问:机器如何识别车牌[1]
  • 小清爱提问:目标检测中的YOLO网络长什么样?[2]


扩展阅读

  • AI100问:什么是YOLO模型 [3]
  • AI100问:机器如何识别车牌[4]

视频展示

  • YOLO visulaization [5]
  • YOLO-v3 [6]


演示链接

  • 旷世科技在线演示[7]
  • 云脉展示[8]
  • 薪火科技[9]
  • DTK车牌识别在线演示[10]

开发者资源

  • OpenCV 车牌识别流程和样例程序[11][12]
  • 基于Yolo v4的车牌识别 [13]
  • ALPR in Unscontrained Scenarios [14]


高级读者

  • Arafat M Y, Khairuddin A S M, Khairuddin U, et al. Systematic review on vehicular licence plate recognition framework in intelligent transport systems[J]. IET Intelligent Transport Systems, 2019, 13(5): 745-755. [15]
  • Srikanth P, Kumar A. Automatic vehicle number plate detection and recognition systems: Survey and implementation[M]//Autonomous and Connected Heavy Vehicle Technology. Academic Press, 2022: 125-139. [16]
  • Zherzdev S, Gruzdev A. Lprnet: License plate recognition via deep neural networks[J]. arXiv preprint arXiv:1806.10447, 2018. [17]
  • Xie L, Ahmad T, Jin L, et al. A new CNN-based method for multi-directional car license plate detection[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 19(2): 507-517. [18]
  • J. Redmon, S. Divvala, R. Girshick, A. Farhadi You only look once: unified, real-time object detection Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (2016), pp. 779-788 [19]