A Lightweight Support-Vector-Machine-Based Infrared Image Processing Workflow for Photovoltaic Module Thermal Anomaly Screening
Deep networks dominate photovoltaic (PV) thermographic fault detection but need large annotated datasets and resist interpretation. We present a lightweight, interpretable infrared workflow combining support-vector-machine (SVM) module/background segmentation from four handcrafted features with an a...
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| Автори: | , , , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
MDPI AG
2026-08-01
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| Серія: | Solar |
| Предмети: | |
| Онлайн доступ: | https://www.mdpi.com/2673-9941/6/4/49 |
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