Atomic-scale defects govern many functional properties of materials, yet their systematic identification and quantification remain challenging because supervised learning approaches require extensive ...

Imaging techniques have considerably improved corrosion-induced metal loss defect detection and severity estimation in recent decades. Even though the detection of defects using imaging techniques in ...

Researchers have tested eight stand-alone deep learning methods for PV cell fault detection and have found that their accuracy was as high as 73%. All methods were trained and tested on the ELPV ...

Detecting macro-defects early in the wafer processing flow is vital for yield and process improvement, and it is driving innovations in both inspection techniques and wafer test map analysis. At the ...

US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...