Diagnosing Shortcut Learning in CNN-Based Photovoltaic Fault Recognition from RGB Images: A Multi-Method Explainability Audit
Convolutional neural networks (CNNs) can achieve high accuracy in photovoltaic (PV) fault recognition from RGB imagery, yet their decisions may rely on shortcut cues induced by heterogeneous backgrounds, viewpoints, and class imbalance. This work presents a multi-method explainability audit on the K...
Guardado en:
| Autor principal: | |
|---|---|
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
MDPI AG
2026-03-01
|
| Colección: | AI |
| Materias: | |
| Acceso en línea: | https://www.mdpi.com/2673-2688/7/3/94 |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|