“第二十一章 车牌识别”版本间的差异
来自cslt Wiki
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==演示链接== | ==演示链接== | ||
| + | * 旷世科技在线演示[https://www.faceplusplus.com.cn/license-plate-recognition/] | ||
| + | * 云脉展示[https://www.yunmaiocr.com/goPlate#] | ||
| + | * 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] | * Tanar Automatic Number Plate Reader System [https://saymannet.com/LPR-License-Plate-Recognition] | ||
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==开发者资源== | ==开发者资源== | ||
| + | * OpenCV 车牌识别流程和样例程序[https://codeantenna.com/a/XVQaHQ0m6T][https://github.com/longzix/SVM-/tree/master] | ||
* 基于Yolo v4的车牌识别 [https://learnopencv.com/automatic-license-plate-recognition-using-deep-learning/] | * 基于Yolo v4的车牌识别 [https://learnopencv.com/automatic-license-plate-recognition-using-deep-learning/] | ||
* ALPR in Unscontrained Scenarios [https://github.com/sergiomsilva/alpr-unconstrained] | * ALPR in Unscontrained Scenarios [https://github.com/sergiomsilva/alpr-unconstrained] | ||
2022年8月10日 (三) 03:06的版本
教学资料
扩展阅读
- AI100问：什么是YOLO模型
- AI100问：机器如何识别车牌
视频展示
演示链接
开发者资源
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. [13]
- 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. [14]
- Zherzdev S, Gruzdev A. Lprnet: License plate recognition via deep neural networks[J]. arXiv preprint arXiv:1806.10447, 2018. [15]
- 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. [16]
- 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 [17]
