Future of Information and Communication Conference (FICC) 2025
28-29 April 2025
Publication Links
IJACSA
Special Issues
Future of Information and Communication Conference (FICC)
Computing Conference
Intelligent Systems Conference (IntelliSys)
Future Technologies Conference (FTC)
International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 1, 2025.
Abstract: Object detection based on drone platforms is a valuable yet challenging research field. Although general object detection networks based on deep learning have achieved breakthroughs in natural scenes, drone images in urban environments often exhibit characteristics such as a high proportion of small objects, dense distribution, and significant scale variations, posing significant challenges for accurate detection. To address these issues, this paper proposes a dual-branch object detection algorithm based on YOLOv8 improvements. Firstly, an auxiliary branch is constructed by extending the YOLOv8 backbone to aggregate high-level semantic information within the network, enhancing the feature extraction capability. Secondly, a Multi-Branch Feature Enhancement (MBFE) module is designed to enrich the feature representation of small objects and enhance the correlation of local features. Third, Spatial-to-Depth Convolution (SPDConv) is utilized to mitigate the loss of small object information during downsampling, preserving more small object feature information. Finally, a dual-branch feature pyramid is designed for feature fusion to accommodate the dual-branch input. Experimental results on the VisDrone benchmark dataset demonstrate that DBYOLOv8 outperforms state-of-the-art object detection methods. Our proposed DBYOLOv8s achieve mAP@0.5 of 49.3% and mAP@0.5:0.95 of 30.4%, which are 2.8% and 1.5%higher than YOLOv9e, respectively.
Yawei Tan, Bingxin Xu, Jiangsheng Sun, Cheng Xu, Weiguo Pan, Songyin Dai and Hongzhe Liu, “DBYOLOv8: Dual-Branch YOLOv8 Network for Small Object Detection on Drone Image” International Journal of Advanced Computer Science and Applications(IJACSA), 16(1), 2025. http://dx.doi.org/10.14569/IJACSA.2025.01601124
@article{Tan2025,
title = {DBYOLOv8: Dual-Branch YOLOv8 Network for Small Object Detection on Drone Image},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.01601124},
url = {http://dx.doi.org/10.14569/IJACSA.2025.01601124},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {1},
author = {Yawei Tan and Bingxin Xu and Jiangsheng Sun and Cheng Xu and Weiguo Pan and Songyin Dai and Hongzhe Liu}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.