Supervised learning algorithms have shown limited use in the field of anomaly detection due
to the unpredictability and difficulty in acquiring abnormal samples. In recent years …

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

近年来, 基于深度学习的表面缺陷检测技术广泛应用在各种工业场景中. 本文对近年来基于深度
学习的表面缺陷检测方法进行了梳理, 根据数据标签的不同将其分为全监督学习模型方法 …

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 …

Deep learning techniques, especially Convolutional Neural Networks (CNN), dominate the
benchmarks for most computer vision tasks. These state-of-the-art results are typically …

In current years, the improvement of deep learning has brought about tremendous changes:
As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) …

Anomaly detection has become an indispensable tool for modern society, applied in a wide
range of applications, from detecting fraudulent transactions to malignant brain tumors. Over …

Perceptual organization is a challenging visual task that aims to perceive and group the
individual visual element so that it is easy to understand the meaning of the scene as a …

Camouflaged object detection is a challenging visual task since the appearance and
morphology of foreground objects and background regions are highly similar in nature …

Texture recognition is a challenging visual task since its multiple primitives or attributes can
be perceived from the texture image under different spatial contexts. Existing approaches …