Aircraft Detection for Remote Sensing Images Based on Deep Convolutional Neural Networks

Table 4

The comparison of multiple algorithms on AP for the other three classes.

Method	Backbone	AP			FPS
		Oil tank (%)	Overpass (%)	Playground (%)
DConvNet [31]	ResNet-101	90.30	89.50	99.80	6.7
DSSD [32]	ResNet-101	72.49	72.10	83.56	6.1
FFSSD [33]	VGG-16	73.24	73.17	84.08	38.2
ESSD [34]	VGG-16	72.94	73.61	84.27	37.3
DC-SPP-YOLO [35]	Figure 5 in [35]	73.52	74.82	84.82	33.5
UAV-YOLO [36]	Figure 1 in [36]	74.20	76.32	85.96	30.12
RFN [37]	ResNet-101	90.50	100.00	99.70	6.5
SigNMS [38]	VGG-16	90.60	87.40	99.10	6.7
Improved-YOLOv3 [39]	Figure 4 in [39]	87.57	89.37	91.56	25.8
MRFF-YOLO [40]	Figure 5 in [40]	86.56	87.56	92.05	25.1
MSRDN-M(Ours)	Figure 11	90.68	84.12	100.00	25