The comprehensive intelligent development of the manufacturing industry puts forward new
requirements for the quality inspection of industrial products. This paper summarizes the …

Over the last few decades, detecting surface defects has attracted significant attention as a
challenging task. There are specific classes of problems that can be solved using traditional …

Defect detection is the task of identifying defects in production samples. Usually, defect
detection classifiers are trained on ground-truth data formed by normal samples (negative …

High-precision cylindrical parts are critical components across various industries including
aerospace, automotive, and manufacturing. Since these parts play a pivotal role in the …

The assessment of how two distinct images are equal are indeed called image similarity and
consistency. In other words, it measures how much the intensity patterns in two images are …

Deep learning is frequently recommended for standard defect detection because of its ace
accuracy and robustness. Unfortunately, current deep learning methods exist several …

Detecting defects in printed labels is essential for quality control. Although a few vision-
based models have been proposed for this challenging task, they fail to deal with the large …

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 …

Structural defects account for a large proportion of defects, and acquiring large batches of
high-quality labels is labor-intensive and time-consuming for industrial visual defect …

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 …