Automated computer-vision-based defect detection has received much attention with the
increasing surface quality assurance demands for the industrial manufacturing of flat steels. …

For a typical surface automated visual inspection (AVI) instrument of planar materials, defect
classification is an indispensable part after defect detection, which acts as a crucial …

The computer-vision-based surface defect detection of metal planar materials is a research
hotspot in the field of metallurgical industry. The high standard of planar surface quality in the …

Defective steel brings economic and commercial reputation losses to the hot-strip
manufacturers, and one of the main difficulties in using machine-vision-based technique for steel …

A robust constant false alarm rate (RCFAR) detector based on bilateral-trimmed-statistics (BTS-RCFAR)
with a closed-form solution is proposed. BTS-RCFAR aims at improving the …

Rain-like layer removal from hot-rolled steel strip surface has been proven to be a workable
measure for suppressing the false alarms frequently triggered in automated visual …

Efficient defect classification is one of the most important preconditions to achieve online
quality inspection for hot-rolled strip steels. It is extremely challenging owing to various defect …

Accurate low-contrast defect detection has become a common bottleneck to further improve
the performance of automated visual inspection (AVI) instruments. Inspired by visual crypsis, …

This paper proposes a multi-scale rotation-invariant haar-like (MSRI-HL) feature integrated
convolutional neural network (MSRIHL-CNN)-based ship detection algorithm of the multiple-…

It is well-known that the convolutional neural network (CNN) is an effective method for
synthetic aperture radar (SAR) target classification. In the convolutional layer of CNN, …