Comparative Analysis of YOLO-Based Algorithms for Vehicle Detection in Aerial Imagery

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Comparative analysis evaluates detection accuracy and speed of YOLO models in aerial imagery, highlighting performance metrics.

The study identifies the fastest YOLO model for vehicle detection, focusing on their performance in aerial imagery under various conditions.
Key performance metrics, including average precision and inference time, show how each YOLO version handles challenging detection tasks.
The evaluation uses the EAGLE dataset, providing insights into YOLO's application for dynamic urban environments.
Findings suggest specific YOLO advancements improve real-time detection capabilities compared to traditional systems.

Dustali et al. (2025) studied this question.

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