VLDFNet: Views-Graph and Latent Feature Disentangled Fusion Network for Multimodal Industrial Anomaly Detection-Reference-Cited by-同舟云学术

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VLDFNet: Views-Graph and Latent Feature Disentangled Fusion Network for Multimodal Industrial Anomaly Detection

Published:2025 Issue: Volume:74 Page:1-13
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Xia Chenxing¹^ORCID,Liu Chaofan¹^ORCID,Zhou Yicong²^ORCID,Li Kuan-Ching³^ORCID

Affiliation:

1. School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, China

2. Department of Computer and Information Science, University of Macau, Macau, China

3. Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan

Funder

National Natural Science Foundation of China

Anhui Postdoctoral Science Foundation

Anhui Province Young Key Teachers Overseas Study and Research Funding Project

Medical Special Cultivation Project of Anhui University of Science and Technology

Huainan City Science and Technology Plan Project

Science and Technology Development Fund, Macau SAR

Universidade de Macau

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/19/10764799/11004494.pdf?arnumber=11004494

Reference40 articles.

1. Thickness Measurement and Surface-Defect Detection for Metal Plate Using Pulsed Eddy Current Testing and Optimized Res2Net Network

2. Transformer-Based Multiscale Reconstruction Network for Defect Detection of Infrared Images

3. Aeroengine Blades Damage Detection and Measurement Based on Multimodality Fusion Learning

4. Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization

5. FastFlow: Unsupervised anomaly detection and localization via 2D normalizing flows;Yu;arXiv:2111.07677,2021

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