The global demand for energy is surpassing its availability owing to the increase in
population and advancements in technology. It is essential to move closer to a dependable …

The rise of deep learning approaches has boosted the modern computing capabilities and
paved the way to novel outstanding applications. Recently, deep neural networks (DNN) …

The rise of deep learning approaches has boosted the modern computing capabilities and
paved the way to novel outstanding applications. Recently, deep neural networks (DNN) …

In this study, an automatic solar defect detection and classification system using deep
learning was proposed. This study focuses on solar faults in photovoltaic systems identified …

Electroluminescence (EL) imaging of photovoltaic solar cells can detect and classify solar
panel faults. This method allows technicians and manufacturers to identify defective panels …

Nowadays, photovoltaic (PV) systems are gaining increasing momentum due to their ability
to generate clean and affordable electric power. However, many factors can impede the …

The utilization of electroluminescence (EL) imaging has proven to be a reliable and precise
method for inspecting photovoltaic (PV) modules, due to its high spatial resolution, which …

In recent studies, it has been noticed that to identify the defects in the solar photovoltaic (PV)
modules, the manufacturers more rely on the automatic defect detection techniques instead …

The common defects observed on the photovoltaic cells during the manufacturing process
include chipping, tree crack, micro-line, soldering, and short circuits. Most of the defects …

Recently, a vast growth has been witnessed in the field of solar energy. The huge demand
on photovoltaic (PV) systems has been broadly integrated into all aspects of modern life …