Multi-scale spatial sensing anomaly detection network guided by high frequency
Information Sciences|更新时间:2026-03-05
|
Multi-scale spatial sensing anomaly detection network guided by high frequency
“The research progress in the field of industrial anomaly detection was introduced, and relevant experts proposed an industrial anomaly detection network that combines high-frequency residual guidance and multi-scale attention feature fusion, providing an effective solution to the problem of low accuracy in detecting small-sized defects in existing industrial anomaly detection algorithms.”
Optics and Precision EngineeringVol. 34, Issue 2, Pages: 296-308(2026)
Gaussian cross-based feature fusion method for hyperspectral image classification
Underwater image enhancement network based on improved U-Net with global feature fusion
Lightweight road crack detection method with adaptive features
Real-time image semantic segmentation based on three-branch network
Edge detection network based on transformer
Related Author
WANG Wenlong
WANG Hairong
YI Zhihang
YANG Zhenye
YANG Jianling
GAO Shaoshu
JIAO Guangsen
LI Guangfeng
Related Institution
College of Computer Science and Engineering, North Minzu University
Ningxia Key Laboratory of Meteorological Disaster Prevention and Reduction (Ningxia Institute of Meteorological Sciences)
Qingdao Institute of Software, College of Computer Science and Technology, Shandong Key Laboratory of Intelligent Oil & Gas Industrial Software, China University of Petroleum (East China)
Petroleum Industry Training Center, China University of Petroleum (East China)
School of Information and Software Engineering, East China Jiaotong University