Improving detection speed is the focus of the one-stage method, while the two-stage method emphasizes detection accuracy. In the practical detection of photovoltaic module defects, we should consider not only the detection speed but also the detection accuracy. The VarifocalNet is an anchor-free detection method and has higher detection accuracy 5.
When solar photovoltaic panel surface defect detection is applied to industrial inspection, the primary focus lies in achieving a highly accurate and precise model with exceptional localization capabilities, and the training model will basically not affect the detection speed.
Policies and ethics Nowadays, the photovoltaic industry has developed significantly. Solar photovoltaic panel defect detection is an important part of solar photovoltaic panel quality inspection. Aiming at the problems of chaotic distribution of defect targets on photovoltaic panels,...
Besides, to balance the detection accuracy, a bidirectional feature pyramid network and attention mechanism were also introduced into YOLOv5s.To improve the accuracy of photovoltaic module defects detection based on lightweight YOLO, Wang et al. 29 proposed PV-LOLO based on YOLOX.
Efforts have been made to develop models capable of real-time defect detection, with some achieving impressive accuracy and processing speeds. However, existing approaches often struggle with feature redundancy and inefficient representations of defects in photovoltaic panels.
Through qualitative and quantitative comparisons with various alternative methods, we demonstrate that our YOLO-ACF strikes a good balance between detection performance, model complexity, and detection speed for defect detection on photovoltaic panels. Moreover, it demonstrates remarkable versatility across a spectrum of defect types.