1 citations · 1 across the 3 of their papers we have counts for
4 papers
IAENet: An Importance-Aware Ensemble Model for 3D Point Cloud-Based Anomaly Detection
Xuanming Cao, Chengyu Tao, Yifeng Cheng +1
Surface anomaly detection is pivotal for ensuring product quality in industrial manufacturing. While 2D image-based methods have achieved remarkable success, 3D point cloud-based d…
GSF-MIAD: Geometry-Guided Score Fusion for Multimodal Industrial Anomaly Detection
Chengyu Tao, Xuanming Cao, Juan Du
Industrial quality inspection plays a critical role in modern manufacturing by identifying defective products during production. While single-modality approaches using either 3D po…
Deep Subspace Learning for Surface Anomaly Classification Based on 3D Point Cloud Data
Xuanming Cao, Chengyu Tao, Juan Du
Surface anomaly classification is critical for manufacturing system fault diagnosis and quality control. However, the following challenges always hinder accurate anomaly classifica…
A Novel Representation of Periodic Pattern and Its Application to Untrained Anomaly Detection
Peng Ye, Chengyu Tao, Juan Du
There are a variety of industrial products that possess periodic textures or surfaces, such as carbon fiber textiles and display panels. Traditional image-based quality inspection…