to Table 5, Pi-GS, Pi-FT, and Pi-Index are individually 2.17%, 0.81%, and 5.25% higher than Faster RCNN’s AP metric, indicating that PU learning can effectively improve the detection performance under severe label missing conditions.
Figure 9 (II) displays the detection results of the seven methods with an APC value of 0.3. The first scenario, shown in the first column of Figure 9 (II), contains an insulator string that consists of six insulators. The insulator at position (6) is partially exposed, while the rest are clearly visible in the image. The insulators, except for the one labeled as “Broken” in position (3), are labeled as “Good”.
For the insulator string, M/D-YOLO v3 did not recognize the insulator string, as shown in (b) and (c). Meanwhile, the other methods were able to identify it successfully. However, D-YOLO v4 and YOLO v5 had large localization errors when detecting the insulator string. Specifically, the left and right boundaries of the predicted box by D-YOLO v4 both exceeded the boundaries of the GTBox. The predicted box by YOLO v5 was completely enclosed within the GTBox. For small-size insulators, M-YOLO v3 and M-YOLO v4 missed all insulators. D-YOLO v3 and D-YOLO v4 detected only two insulators, while YOLO
v5 and Pi-FT detected three insulators. Therefore, Pi-Index outperformed the other methods with four insulators detected correctly.
There is one insulator string and seven insulators in the second scenario, shown in the second column of Figure 9 (II). The insulators are arranged closely and the positions (1)-(5) labeled as “Good”, while the insulator at position (7) labeled as “FlashDamaged”. From the detection results of the insulator string, it can be seen that the results from all the methods are poor. Only Pi-FT and Pi-Index were able to successfully recognize the insulator string. For the insulators, M/D-YOLO v3 and M-YOLO v4 did not detect any insulators, while D-YOLO v4 only detected the insulator at position (3). This indicates that these methods have a high rate of missed detections. The performance of YOLO v5 and Pi-FT is slightly better. In detail, they only missed the insulator at position (7). Pi-Index further successfully identified the insulator at position (7). The detection results demonstrated that Pi-Index performed best for detecting insulators in contrast to the other detectors.