基于改进YOLOv5的红外车辆检测方法-Reference-Cited by-同舟云学术

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基于改进YOLOv5的红外车辆检测方法

Published:2023 Issue:8 Volume:52 Page:20230245
ISSN:1007-2276
Container-title:Infrared and Laser Engineering
language:en
Short-container-title:红外与激光工程

Author:

Zhang Xuezhi 张学志,Zhao Hongdong 赵红东,Liu Weina 刘伟娜,Zhao Yiming 赵一鸣,Guan Song 关松

Publisher

Shanghai Institute of Optics and Fine Mechanics

Subject

Electrical and Electronic Engineering,Space and Planetary Science,Aerospace Engineering,Atomic and Molecular Physics, and Optics

Reference20 articles.

1. An efficient and scene-adaptive algorithm for vehicle detection in aerial images using an improved YOLOv3 framework;X X Zhang;ISPRS International Journal of Geo-information,2019

2. Study on the evaluation method of sound phase cloud maps based on an improved YOLOv4 algorithm;Sensors,2020

3. Girshick R Donahue J Darrell T et al. Rich feature hierarchies f accurate object detection semantic segmentation[C]2014 IEEE Conference on Computer Vision Pattern Recognition (CVPR) 2014: 580587.

4. Girshick R. Fast RCNN [C]2015 IEEE International Conference on Computer Vision (ICCV) 2015: 14401448.

5. Faster R-CNN: towards real-time object detection with region proposal networks;IEEE Transactions on Pattern Analysis and Machine Intelligence,2017

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. 注意力引导的多尺度红外行人车辆实时检测;Infrared and Laser Engineering;2024

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