Multi-Scale Feature-Enhanced YOLOv8 for Object Detection in Photovoltaic Farm Panoramic Imagery
Keywords:
Photovoltaic power station, Panoramic inspection, YOLOv8, Multi-scale feature enhancement, Object detectionAbstract
With the continuous expansion of the photovoltaic industry, efficient and accurate inspection of photovoltaic power stations has become key to ensuring their stable operation. This paper proposes a multi-scale feature-enhanced YOLOv8 algorithm for panoramic inspection of photovoltaic power stations. By optimizing the network structure, the feature extraction capability for photovoltaic modules and defects of different scales is enhanced. Experiments on a self-built dataset show that the improved algorithm achieves an mAP@0.5 of 0.852, an improvement of 7.6% over the original YOLOv8, striking a good balance between detection speed and accuracy, and providing a reliable technical solution for intelligent operation and maintenance of photovoltaic power stations.
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