ST-YOLO: A defect detection method for photovoltaic
The adoption of a deep learning-based infrared image detection algorithm for PV modules significantly reduces the cost of manual inspection
Photovoltaic panel defect detection algorithm based on infrared
To address these limitations (Hussain & Khanam, 2024), this study proposes a PV panel defect detection method based on YOLOv8 and computer-based infrared vision. We modify the
GS-YOLO: Lightweight Small-Target Detection for Photovoltaic
Against the backdrop of global clean energy transition, photovoltaic defect detection is crucial for ensuring the operational reliability of power plants. This paper addresses two major challenges in
Infrared Computer Vision for Utility-Scale Photovoltaic Array
Among these, infrared thermography cameras are a powerful tool for improving solar panel inspection in the field. These can be combined with other technologies, including image processing and machine
Thermographic inspection of photovoltaics and solar
Using an infrared camera from InfraTec, faults of new and existing photovoltaic systems can be displayed thermographically.
Intelligent monitoring of photovoltaic panels based on infrared detection
The new technique uses a U-Net neural network and a classifier in combination to intelligently analyse the PV panel''s infrared thermal images taken by drones or other kinds of remote
Accurate detection of photovoltaic panel defects via visible-infrared
This study proposes a lightweight dual-modal detection scheme, combining visible and infrared images to address three major challenges in photovoltaic panel defect detection, namely
Intelligent monitoring of photovoltaic panels based on infrared
In this paper, the equipment used for collecting the infrared thermal images of PV panels was an infrared camera (FLUKE Ti 450), which is often used to acquire the thermal images of PV arrays in operation,
Fault Detection in Solar Energy Systems: A Deep Learning Approach
This study explores the potential of using infrared solar module images for the detection of photovoltaic panel defects through deep learning, which represents a crucial step toward
A bright spot detection and analysis method for infrared
This paper based on U-Net network and HSV space, proposes a method of PV infrared image segmentation and location detection of hot spots, which is used
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