UAV Target Tracking and Detection Based on Faster R-CNN Improved Networks-Reference-Cited by-同舟云学术

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UAV Target Tracking and Detection Based on Faster R-CNN Improved Networks

Published:2024-04-26 Issue: Volume:43 Page:751-755
ISSN:
Container-title:2024 IEEE 2nd International Conference on Control, Electronics and Computer Technology (ICCECT)
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Author:

Ma Ji¹,Li Haoxuan¹,Xi Jianchao¹,Zha Guangjie¹,Yue Yang¹,Yang Hong¹

Affiliation:

1. Harbin University of Science and Technology,Harbin,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10545644/10545608/10545680.pdf?arnumber=10545680

Reference10 articles.

1. Research on monocular pose estimation algorithm based on improved YOLO6D;Pan;Sensors and Microsystems,2024

2. UAV dense small target detection algorithm based on YOLOv5s;Han;Journal of Zhejiang University(Engineering Science),2023

3. UAV small target detection algorithm based on improved Faster R-CNN;Zhang;Journal of Quantum Electronics,2022

4. Small target detection in UAV aerial images based on Faster R-CNN (in English);Wang;Journal of Measurement Science and Instrumentation,2020

5. FRWCAE: joint faster-RCNN and Wasserstein convolutional auto-encoder for instance retrieval

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. TMP: Temporal Motion Perception with spatial auxiliary enhancement for moving Infrared dim-small target detection;Expert Systems with Applications;2024-12

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