YOLOv5s_2E: Improved YOLOv5s for Aerial Small Target Detection-Reference-Cited by-同舟云学术

YOLOv5s_2E: Improved YOLOv5s for Aerial Small Target Detection

Published:2023 Issue: Volume:11 Page:80479-80490
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Shi Tao¹^ORCID,Ding Yao¹^ORCID,Zhu Wenxu²^ORCID

Affiliation:

1. Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems, School of Electrical Engineering and Automation, Tianjin University of Technology, Tianjin, China

2. College of Electrical Engineering, North China University of Science and Technology, Tangshan, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hebei Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10198270.pdf?arnumber=10198270

Reference33 articles.

1. CARAFE: Content-Aware ReAssembly of FEatures

2. YOLOv4: Optimal speed and accuracy of object detection;bochkovskiy;arXiv 2004 10934,2020

3. YOLOv3: An incremental improvement;redmon;arXiv 1804 02767,2018

4. RSOD: Real-time small object detection algorithm in UAV-based traffic monitoring

5. UN-YOLOv5s: A UAV-Based Aerial Photography Detection Algorithm

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