Predictive maintenance is a field of study whose main objective is to optimize the timing and
type of maintenance to perform on various industrial systems. This aim involves maximizing …

Recently, large-scale vision-language models such as CLIP have demonstrated immense
potential in zero-shot anomaly segmentation (ZSAS) task, utilizing a unified model to directly …

In modern manufacturing, vision-based defect recognition is an important technology to
guarantee product quality. Deep learning-based vision recognition methods have made …

Metal defect segmentation poses a great challenge for automated inspection systems due to
the complex light reflection from the surface and lack of training data. In this work we …

Quality inspection is inevitable in the steel industry so there are already benchmark datasets
for the visual inspection of steel surface defects. In our work, we show, contrary to previous …

Detecting product surface defects is an important issue in industrial scenarios. In the actual
scene, the shooting angle and the distance between the industrial camera and the shooting …

Using machine learning (ML) techniques in general and deep learning techniques in
specific needs a certain amount of data often not available in large quantities in technical …

Recently, outstanding identification rates in image classification tasks were achieved by
convolutional neural networks (CNNs). to use such skills, selective CNNs trained on a …

Industrial defect detection has great significance in product quality improvement, and deep
learning methods are now the dominant approach. However, the volume of industrial …

Surface defect identification is essential for maintaining and improving the quality of
industrial products. However, numerous environmental factors, including reflection …