Object Detection Method Based on Improved YOLO Lightweight Network-Reference-Cited by-同舟云学术

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Object Detection Method Based on Improved YOLO Lightweight Network

Published:2020 Issue:14 Volume:57 Page:141003
ISSN:1006-4125
Container-title:Laser & Optoelectronics Progress
language:en
Short-container-title:激光与光电子学进展

Author:

Li Chengyue 李成跃,Yao Jianmin 姚剑敏,Lin Zhixian 林志贤,Yan Qun 严群,Fan Baoqing 范保青

Publisher

Shanghai Institute of Optics and Fine Mechanics

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics

Cited by 15 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. Multiclass objects detection algorithm using DarkNet-53 and DenseNet for intelligent vehicles;EURASIP Journal on Advances in Signal Processing;2023-08-01

2. Defect Detection of Key Components of EMU Based on Improved YOLOv5;Proceedings of the 2023 9th International Conference on Computing and Artificial Intelligence;2023-03-17

3. An Improved Tuna-YOLO Model Based on YOLO v3 for Real-Time Tuna Detection Considering Lightweight Deployment;Journal of Marine Science and Engineering;2023-03-02

4. 融合双注意力机制的Landsat8 OLI遥感图像云检测;Laser & Optoelectronics Progress;2023

5. Study on Detection and Recognition of Traffic Lights Based on Improved YOLOv4;Sensors;2022-10-13

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