Accurate and efficient characterisation techniques are essential to ensure the optimal
performance and reliability of photovoltaic devices, especially given the large number of …

In recent years, with the rapid development of deep learning, computer vision technology
based on convolutional neural network (CNN) is widely used in industrial fields. At present …

Photovoltaic (PV) cell modules are the core components of PV power generation systems,
and defects in these modules can significantly affect photovoltaic conversion efficiency and …

Nowadays, the rapid development of photovoltaic (PV) power stations requires increasingly
reliable maintenance and fault diagnosis of PV modules in the field. Due to the …

To improve the precision of defect categorization and localization in images, this paper
proposes an approach for detecting surface defects in hot-rolled steel strips. The approach …

Visual inspection of photovoltaic modules using electroluminescence (EL) images is a
common method of quality inspection. Because human inspection requires a lot of time …

Quality inspection applications in industry are required to move towards a zero-defect
manufacturing scenario, with non-destructive inspection and traceability of 100% of …

Defect recognition is an important task in intelligent manufacturing. Due to the subjectivity of
human annotation, the collected defect data usually contains a lot of noise and …

Deep learning has seen its promising applications in manufacturing processes. In this study,
a deep network named Cascade Tri-DFPN based on the two-stage target detection …

End‐of‐line characterization of solar cells is necessary to filter out defective cells and bin
cells to avoid power mismatch loss in photovoltaic modules. Current–voltage testers, used …