April 6, 2022, 1:12 a.m. | Antonio Di Tommaso, Alessandro Betti, Giacomo Fontanelli, Benedetto Michelozzi

cs.LG updates on arXiv.org arxiv.org

As solar capacity installed worldwide continues to grow, there is an
increasing awareness that advanced inspection systems are becoming of utmost
importance to schedule smart interventions and minimize downtime likelihood. In
this work we propose a novel automatic multi-stage model to detect panel
defects on aerial images captured by unmanned aerial vehicle by using the
YOLOv3 network and Computer Vision techniques. The model combines detections of
panels and defects to refine its accuracy and exhibits an average inference
time per …

arxiv cv detection imaging panels stage

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