Pedestrian Detection Algorithm Based on YOLOv3
Author:
Affiliation:
1. Bohai University,College of Control Science and Engineering,Jinzhou,China,121013
2. Fujian Normal University,College of Photonic and Electronic Engineering,Fuzhou,China,350117
3. Changchun Normal University,Changchun,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10071141/10071335/10071374.pdf?arnumber=10071374
Reference14 articles.
1. CSPNet: A New Backbone that can Enhance Learning Capability of CNN;wang;2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW),2020
2. YOLOv3: An Incremental Improvement;redmon,2018
3. ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
4. Multi-scale Pedestrian Detection Based on Receptive Field Matching
5. Crowded pedestrian detection algorithm based on improved FCOS[J];qi;CAAI Transactions on Intelligent Systems,2021
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