1. 인용 논문 Traffic-sign detection and classification in the wild Zhe Zhu, Dun Liang, Songhai Zhang, Xiaolei Huang, Baoli Li, Shimin Hu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 2110-2118 2. 인용 부분 -Page 1 In comparison with normal detection tasks, the traffic signs oc- cupy small proportion of each image in the real-driving scenario [7]. -Page 3 There are thr..
1. 인용 논문 Traffic-sign detection and classification in the wild Zhe Zhu, Dun Liang, Songhai Zhang, Xiaolei Huang, Baoli Li, Shimin Hu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 2110-2118 2. 인용 부분 -Page 5 -Page 8 We evaluated our method on the Tsinghua–Tencent 100K test dataset. It achieved 87.0% mAP at a Jaccard similarity coefficient of 0.5 and the average ..
1. 인용 논문 Traffic-sign detection and classification in the wild Zhe Zhu, Dun Liang, Songhai Zhang, Xiaolei Huang, Baoli Li, Shimin Hu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 2110-2118 2. 인용 부분 -Page 2 We are the first to present a network that performs joint traffic light and sign detection. Our architecture is suitable for autonomous car deployment becau..
1. 인용 논문 Traffic-sign detection and classification in the wild Zhe Zhu, Dun Liang, Songhai Zhang, Xiaolei Huang, Baoli Li, Shimin Hu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 2110-2118 2. 인용 부분
1. 인용 논문 Traffic-sign detection and classification in the wild Zhe Zhu, Dun Liang, Songhai Zhang, Xiaolei Huang, Baoli Li, Shimin Hu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 2110-2118 2. 인용 부분 - Page 4-5 To detect small objects from a high-resolution image, we design a two-stage architecture as shown in Fig. 3. For region proposal stage, two top-down feat..
1. 인용 논문 Traffic-sign detection and classification in the wild Zhe Zhu, Dun Liang, Songhai Zhang, Xiaolei Huang, Baoli Li, Shimin Hu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 2110-2118 2. 인용 부분 - Page 1-2 - Page 4 To verify the effectiveness of our framework, we perform experiments on Tsinghua-Tencent 100K traffic sign dataset [22].
1. 인용 논문 Traffic-sign detection and classification in the wild Zhe Zhu, Dun Liang, Songhai Zhang, Xiaolei Huang, Baoli Li, Shimin Hu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 2110-2118 2. 인용 부분
1. 인용 논문 Traffic-sign detection and classification in the wild Zhe Zhu, Dun Liang, Songhai Zhang, Xiaolei Huang, Baoli Li, Shimin Hu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 2110-2118 2. 인용 부분 https://arclab.tistory.com/172?category=679057 - 성능 측정 결과
1. 인용 논문 Traffic-sign detection and classification in the wild Zhe Zhu, Dun Liang, Songhai Zhang, Xiaolei Huang, Baoli Li, Shimin Hu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 2110-2118 2. 인용 부분 -Page 1,3 Thus, in this paper, a sign detection database [9] consisting of images collected under real world conditions is employed to evaluate the proposed approac..
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