A Photovoltaic Panel Defect Detection Method Based on the Improved
Aiming at the current PV panel defect detection methods with insufficient accuracy, few defect categories, and the problem that defect targets cannot be localized, this paper proposes a PV panel
A lightweight and efficient model for photovoltaic panel defect
Within this research, we introduce a streamlined yet effective model founded on the “You Only Look Once” algorithm to detect photovoltaic panel defects in intricate settings.
Enhanced photovoltaic panel defect detection via adaptive
In order to validate the efficacy of the proposed module, we conducted experiments using a dataset comprising 4500 electroluminescence images of photovoltaic panels.
A photovoltaic panel defect detection framework enhanced by deep
This paper proposes a photovoltaic panel defect detection method based on an improved YOLOv11 architecture. By introducing the CFA and C2CGA modules, the YOLOv11 model is
A Lightweight Transformer Model for Defect Detection in
To ensure solar panels function well, efficient and accurate defect detection of PV modules is essential. Visual-based deep learning detection methods, such as Transformer and Convolutional Neural
A novel deep learning model for defect detection in photovoltaic
To address the current limitations of low precision and high image data requirements in defect detection algorithms based on visible light imaging, this paper proposes a novel visible light
LEM-Detector: An Efficient Detector for Photovoltaic Panel Defect Detection
To address these challenges, this paper proposes the LEM-Detector, an efficient end-to-end photovoltaic panel defect detector based on the transformer architecture.
Fault Detection and Classification for Photovoltaic Panel System Using
Advances in automation, prediction, and management have enabled sophisticated fault detection methods to enhance system reliability and availability. This paper emphasizes the pivotal
Optimized YOLO based model for photovoltaic defect detection in
In this study, PV-YOLOv12n is introduced as an optimized variant of YOLOv12n, tailored for defect detection in electroluminescence (EL) images of PV panels.
YOLO-LitePV: a lightweight detection algorithm for photovoltaic panel
To address the low operational efficiency of detection algorithms and the low accuracy due to the similarity and large-scale variance of PV defects, we propose an improved lightweight