Research on Traffic Vehicle Target Detection Method based on Improved YOLOv7

Author:

Zhang Feng1ORCID,Sun Quan1ORCID,Yuan Shuai1ORCID

Affiliation:

1. Shenyang Jianzhu University, China

Publisher

ACM

Reference15 articles.

1. Faisal A, Kamruzzaman M, Yigitcanlar T, Understanding autonomous vehicles[J]. Journal of transport and land use, 2019, 12(1): 45-72.

2. Lu X, Li B, Yue Y, Grid r-cnn[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019: 7363-7372.

3. Girshick R. Fast r-cnn[C]//Proceedings of the IEEE international conference on computer vision. 2015: 1440-1448.

4. Ren S, He K, Girshick R, Faster r-cnn: Towards real-time object detection with region proposal networks[J]. Advances in neural information processing systems, 2015, 28.

5. Tian Y, Yang G, Wang Z, Apple detection during different growth stages in orchards using the improved YOLO-V3 model[J]. Computers and electronics in agriculture, 2019, 157: 417-426.

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