A Modified YOLOv8 Detection Network for UAV Aerial Image Recognition
Guizhou University of Finance and Economics · Guizhou University
Abstract
UAV multitarget detection plays a pivotal role in civil and military fields. Although deep learning methods provide a more effective solution to this task, changes in target size, shape change, occlusion, and lighting conditions from the perspective of drones still bring great challenges to research in this field. Based on the above problems, this paper proposes an aerial image detection model with excellent performance and strong robustness. First, in view of the common problem that small targets in aerial images are prone to misdetection and missed detection, the idea of Bi-PAN-FPN is introduced to improve the neck part in YOLOv8-s. By fully considering and reusing multiscale features, a more advanced and…
Citation impact
- FWCI
- 44.74
- Percentile
- 100%
- References
- 36
Authors
5Topics & keywords
- Computer science
- Artificial intelligence
- Robustness (evolution)
- Aerial image
- Minimum bounding box
- Interpretability
- Pattern recognition (psychology)
- Outlier