SPHERE: Benchmarking YOLO vs. CNN on a Novel Dataset for High-Accuracy Solar Panel Defect Detection in Renewable Energy Systems
Solar panels are critical for renewable electricity generation, yet defects significantly reduce power output and risk grid instability, necessitating reliable AI-driven defect detection. We propose the SPHERE (Solar Panel Hidden-Defect Evaluation for Renewable Energy) method for such cases. This st...
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| Main Authors: | Kubilay Ayturan, Berat Sarıkamış, Mehmet Feyzi Akşahin, Uğurhan Kutbay |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/9/4880 |
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