132 citations · 156 across the 6 of their papers we have counts for
6 papers
Patch-wise Auto-Encoder for Visual Anomaly Detection
Yajie Cui, Zhaoxiang Liu, Shiguo Lian
Anomaly detection without priors of the anomalies is challenging. In the field of unsupervised anomaly detection, traditional auto-encoder (AE) tends to fail based on the assumptio…
Data-Centric AI Paradigm Based on Application-Driven Fine-Grained Dataset Design
Huan Hu, Yajie Cui, Zhaoxiang Liu +1
Deep learning has a wide range of applications in industrial scenario, but reducing false alarm (FA) remains a major difficulty. Optimizing network architecture or network paramete…
Application-Driven AI Paradigm for Human Action Recognition
Zezhou Chen, Yajie Cui, Kaikai Zhao +2
Human action recognition in computer vision has been widely studied in recent years. However, most algorithms consider only certain action specially with even high computational co…
A Waste Copper Granules Rating System Based on Machine Vision
Kaikai Zhao, Yajie Cui, Zhaoxiang Liu +1
In the field of waste copper granules recycling, engineers should be able to identify all different sorts of impurities in waste copper granules and estimate their mass proportion…
A Survey on Unsupervised Anomaly Detection Algorithms for Industrial Images
Yajie Cui, Zhaoxiang Liu, Shiguo Lian
In line with the development of Industry 4.0, surface defect detection/anomaly detection becomes a topical subject in the industry field. Improving efficiency as well as saving lab…
Deep Partial Multi-View Learning
Changqing Zhang, Yajie Cui, Zongbo Han +3
Although multi-view learning has made signifificant progress over the past few decades, it is still challenging due to the diffificulty in modeling complex correlations among diffe…