Lightweight Object Detection Algorithm Based on Hybrid Pruning Strategy
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-0923-0_70
Reference28 articles.
1. Nandi, D., Saif, A., Paul, P., et al.: Traffic sign detection based on color segmentation of obscure image candidates: a comprehensive study. Int. J. Mod. Educ. Comput. Sci. (IJMECS) 10(6), 35–46 (2018)
2. Boujemaa, K.S., Bouhoute, A., Boubouh, K., et al.: Traffic sign recognition using convolutional neural networks. In: International Conference on Wireless Networks and Mobile Communications (2017)
3. Yakimov, P., Fursov, V.: Traffic signs detection and tracking using modified hough transform. In: International Joint Conference on e-Business and Telecommunications (ICETE), pp. 22–28 (2015)
4. Zhang, S., Wen, L.Y., Bian, X., et al.: Single-shot refinement neural network for object detection. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 4203–4212 (2018)
5. Zhu, H., Zhang, C.: Real-time traffic sign detection based on YOLOv2. In: International Conference on Image and Video Processing, and Artificial Intelligence (IVPAI), vol. 29, p. 108361B (2018)
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