harunsahinol/solar-panel-detection-with-YOLOv8
This project aims to detect hotspot areas in solar panels using the YOLOv8 object detection model. The model has been trained on a dataset obtained from
Visual inspection is one method for spotting damage, such as cracks, incorrectly soldered connections, mismatched components, cable or frame damage, which may later cause more resistance and hot spots...
This project aims to detect hotspot areas in solar panels using the YOLOv8 object detection model. The model has been trained on a dataset obtained from
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
This paper presents an active hot-spot detection method to detect hot spotting within a series of PV cells, using ac parameter characterization. A PV cell is comprised of series and parallel
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
The existing hot-spot fault detection methods of photovoltaic panels cannot adequately complete the real-time detection task; hence, a detection model considering both detection accuracy and speed is
This model is a detection method for hot spots of PV panels based on the latest generation of the one-stage object detection YOLOv5 network, which is improved to achieve rapid
To address this issue, this paper proposes a method and system for hot spot detection on photovoltaic panels using unmanned aerial vehicles (UAVs) equipped with multispectral cameras.
Aiming at the problem of difficult operation and maintenance of PV power plants in complex backgrounds and combined with image processing technology, a method for detecting hot
These results validate the effectiveness of PV-YOLOv12n in detecting critical PV panel defects, supporting its deployment in large-scale