Comparison of Different Yolo Algorithms For The Detection of Camouflaged Military Targets

This study compares the performance of different YOLO models in the detection of military camouflaged vehicles. According to the experimental results, YOLOv8-s is the most successful model with Recall, [email protected] and F1-Score values of 0.6072,0.6727, and 0.6862 respectively. Although YOLOv9-s has the highest Precision value with 0.8361, it limits the detection success due to low Recall with 0.5122. Although the YOLOv5-s and YOLOv5-m models produced competitive results, the YOLOv8-s model showed a more balanced performance in all metrics. YOLOv10-s showed the lowest performance. The results show that YOLOv8-s is the most effective model for military vehicle detection and performs well in harsh environmental conditions.