Enhanced Segmentation of PV Arrays in Infrared Images using an Improved SegFormer Approach.

An infrared image segmentation model for photovoltaic arrays is proposed based on the improved Segformer. The inception-enhanced attention mechanism and multi-scale spatial feature extraction is leveraged to address problems, such as segmentation holes and environmental misclassification. Furthermore, the encoder of the proposed model is improved using the Feature Pyramid Network and bilinear interpolation operation to enhance the completeness of edge details. Experiments on infrared images gathered from a real-world power station shows that the model achieves improvements of 0.48 in mIoU, 0.3 in mAcc, and 1.38 in mDice, compared to existing models besides the original Segformer.