Table 1.

Detection performance of each model

Models	mAP@0.5	mAP@0.5:0.95	Average Recall
MultiStage Methods
Faster R-CNN ResNet-50	0.958	0.677	0.732
Faster R-CNN ResNet-101	0.930	0.705	0.745
Faster R-CNN XCeption-101	0.941	0.682	0.720
Libra RCNN Xception-101	0.938	0.711	0.767
Faster R-CNN RegnetX 3.2GF	0.973	0.723	0.771
Cascade RCNN Resnet-101	0.917	0.689	0.749
Dynamic R-CNN	0.934	0.688	0.736
Single-Stage Methods
SSD512 VGG16	0.875	0.623	0.721
YOLO DarkNet-53	0.755	0.442	0.605
RetinaNet Resnet-101	0.903	0.665	0.751