Smart data driven traffic sign detection method based on adaptive color threshold and shape symmetry

2019 ◽  
Vol 94 ◽  
pp. 381-391 ◽  
Author(s):  
Xianghua Xu ◽  
Jiancheng Jin ◽  
Shanqing Zhang ◽  
Lingjun Zhang ◽  
Shiliang Pu ◽  
...  
Author(s):  
Jixiang Wan ◽  
Wei Ding ◽  
Hanlin Zhu ◽  
Ming Xia ◽  
Zunkai Huang ◽  
...  

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 112
Author(s):  
Shangwang Liu ◽  
Tongbo Cai ◽  
Xiufang Tang ◽  
Yangyang Zhang ◽  
Changgeng Wang

Aiming at recognizing small proportion, blurred and complex traffic sign in natural scenes, a traffic sign detection method based on RetinaNet-NeXt is proposed. First, to ensure the quality of dataset, the data were cleaned and enhanced to denoise. Secondly, a novel backbone network ResNeXt was employed to improve the detection accuracy and effection of RetinaNet. Finally, transfer learning and group normalization were adopted to accelerate our network training. Experimental results show that the precision, recall and mAP of our method, compared with the original RetinaNet, are improved by 9.08%, 9.09% and 7.32%, respectively. Our method can be effectively applied to traffic sign detection.


2019 ◽  
Vol 1176 ◽  
pp. 032045 ◽  
Author(s):  
Linxiu Wu ◽  
Houjie Li ◽  
Jianjun He ◽  
Xuan Chen

2021 ◽  
Author(s):  
Tonghe Ding ◽  
Kaili Feng ◽  
Tianping Li ◽  
Zhifeng Liu

2013 ◽  
Vol 30 (5) ◽  
pp. 539-551 ◽  
Author(s):  
Gangyi Wang ◽  
Guanghui Ren ◽  
Lihui Jiang ◽  
Taifan Quan

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