In order to solve the problem of difficult deployment of existing deep learning-based defect
detection models in terminal equipment with limited computational capacity, a lightweight …

In the process of industrial production, product defects often arise due to improper
operations among other reasons, rendering the detection of such flaws an indispensable …

Printed circuit board (PCB) surface defect detection is an essential part of the PCB
manufacturing process. Currently, advanced CCD or CMOS sensors can capture high …

Automated vision defect detection is a crucial step in monitoring product quality in industrial
production. Despite the widespread utilization of deep learning methods for surface defect …

Geometric integrity directly impacts the functionality, reliability, and safety of final
manufactured products, making the qualification of parts based on measurements of their …

Defect detection on steel surfaces with complex textures is a critical and challenging task in
the industry. The limited number of defect samples and the complexity of the annotation …

Defect detection in aluminum profiles helps to ensure product quality. However, aluminum
defects suffer from variable object scales and high defect-background similarity issues. To …

Tunnel linings require routine inspection as they have a big impact on a tunnel's safety and
longevity. In this study, the convolutional neural network was utilized to develop the MFF …

Surface defect detection is crucial in industrial production, and due to the conveyor speed,
real-time detection requires 30 to 60 Frames Per Second, which exceeds the capability of …

Gear defect detection is a crucial component in power automation systems. Methods based
on deep learning have exhibited excellent performance in detecting gears. However, the …