Unmanned aerial vehicle (UAV) object detection algorithm based on keypoints representation and rotated distance-IoU loss-Reference-Cited by-同舟云学术

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Unmanned aerial vehicle (UAV) object detection algorithm based on keypoints representation and rotated distance-IoU loss

Published:2024-03-25 Issue:2 Volume:21 Page:
ISSN:1861-8200
Container-title:Journal of Real-Time Image Processing
language:en
Short-container-title:J Real-Time Image Proc

Author:

Zhu Hufei,Huang Yonghui,Xu Ying,Zhou Jianhong,Deng Fuqin,Zhai Yikui

Funder

Key Research Projects for the Universities of Guangdong Provincial Education Department

This study was funded by Guangdong Basic and Applied Basic Research Foundation

Guangdong, Hong Kong, Macao and the Greater Bay Area International Science and Technology Innovation Cooperation Project

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11554-024-01444-6.pdf

Reference38 articles.

1. Feng, J., Yi, C.: Lightweight Detection Network for Arbitrary-Oriented Vehicles in UAV Imagery via Global Attentive Relation and Multi-Path Fusion. Drones. 6, 108 (2022)

2. Taheri Tajar, A., Ramazani, A., Mansoorizadeh, M.: A lightweight Tiny-YOLOv3 vehicle detection approach. J. Real-Time Image Proc. 18, 2389–2401 (2021). https://doi.org/10.1007/s11554-021-01131-w

3. Zerrouk, I., Moumen, Y., Khiati, W.: Evolutionary algorithm for optimized CNN architecture search applied to real-time boat detection in aerial images. J. Real-Time Image Proc. 20, 78 (2023). https://doi.org/10.1007/s11554-023-01332-5

4. Zeng, T., Fang, J., Yin, C., Li, Y., Fu, W., Zhang, H., Wang, J., Zhang, X.: Recognition of Rubber Tree Powdery Mildew Based on UAV Remote Sensing with Different Spatial Resolutions. Drones. 7, 533 (2023)

5. Wang, S., Zhao, J., Ta, N., et al.: A real-time deep learning forest fire monitoring algorithm based on an improved Pruned + KD model. J. Real-Time Image Proc. 18, 2319–2329 (2021). https://doi.org/10.1007/s11554-021-01124-9

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