In this study, we aimed to address the primary challenges encountered in industrial
integrated circuit (IC) surface defect detection, particularly focusing on the imbalance in …

For the problems of low recognition rate and slow recognition speed of traditional detection
methods in IC appearance defect detection, we propose an IC appearance defect detection …

At semiconductor wafer production sites, an automatic defect classification (ADC) system is
used to analyze defects. The ADC system automatically classifies defect images into user …

In the semiconductor manufacturing industry, Automatic Defect Classification (ADC) plays an
important role in maintaining high wafer inspection quality and reducing yield loss. ADC …

The downscaling of device dimensions in semiconductor manufacturing has meant that
critical defect sizes have become smaller and smaller. This makes it more likely that the …

A model based on information theory, which allows yield managers to determine an optimal
portfolio of yield analysis technologies for both the R&D and volume production …

The rise of deep learning, especially in the realm of computer vision, paves ways of
leveraging automatic optical inspection systems to a higher level. Convolutional neural …

Accurate detection and classification of wafer defects constitute an important component of
the IC production process because together they can immediately improve the yield and …

A technique is proposed for high-precision, automatic recognition of circuit patterns on a
semiconductor wafer from multiple scanning electron microscope (SEM) images. This …

An automatic defect classification system (ADC) for use in visual inspection of
semiconductor wafers is introduced. The methods of extracting the defect features based on …