TransLearn-YOLOx: Improved-YOLO with Transfer Learning for Fast and Accurate Multiclass UAV Detection
Author:
Affiliation:
1. Electrical and Computer Engineering COMSATS University Isb., Wah Campus,Wah,Pakistan
2. Brandon University,Department of Computer Science,Brandon,Manitoba,Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10139854/10139858/10139896.pdf?arnumber=10139896
Reference23 articles.
1. Automated Drone Detection Using YOLOv4
2. Deep learning-based strategies for the detection and tracking of drones using several cameras
3. Machine Learning Inspired Sound-Based Amateur Drone Detection for Public Safety Applications
4. A Modified YOLOv4 Deep Learning Network for Vision-Based UAV Recognition
5. Drone Detection Using YOLOv5
Cited by 2 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. Fast Drone Detection With Optimized Feature Capture and Modeling Algorithms;IEEE Access;2024
2. Real Time Drones Detection Based on Cameras and Recent YOLO Algorithm Versions;2023 2nd International Conference on Electronics, Energy and Measurement (IC2EM);2023-11-28
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