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- Title
基于改进 RetinaNet 的行人检测算法.
- Authors
刘晋川; 黎向锋; 叶磊; 刘安旭; 赵康; 左敦稳
- Abstract
To improve the detection precision in actual application scenes, a high resolution feature extraction network High-Resolution Representation Network(HRNet)and a Guided Anchoring mechanism were proposed to improve the RetinaNet algorithm, the high resolution information of the feature maps were maintained during feature extraction and the anchors in network were generated adaptively, which improved the detection precision of the algorithm. The results show that the improved algorithm achieves a mean average precision of 0. 905 on Caltech pedestrian dataset, which is 6. 0% higher than the standard RetinaNet algorithm. The detection speed reaches 19 FPS on video with the image size of 1 280 × 720 pixels per frame, the algorithm achieves the balance between the detection precision and the detection speed.
- Publication
Science Technology & Engineering, 2022, Vol 22, Issue 10, p4019
- ISSN
1671-1815
- Publication type
Article