The DOI matches its Crossref record; 41 of the 43 references it cites were found in a registry or an index.
Encoding Structure-Texture Relation with P-Net for Anomaly Detection in Retinal Images
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U-Net: Convolutional Networks for Biomedical Image Segmentation
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GAN（Generative Adversarial Nets）
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Anomaly Detection via Reverse Distillation from One-Class Embedding
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Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning
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Deep Industrial Image Anomaly Detection: A Survey
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“[81] introduce P-Net to compare the difference in structure between the original and reconstruction images.”
Self-citationBeyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization
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Metadata
- Authors
- Zhou, K., Xiao, Y., Yang, J., Cheng, J., Liu, W., Luo, W., Gu, Z., Liu, J., & Gao, S.
- Affiliations
- ShanghaiTech University (CN)
- Chinese Academy of Sciences (CN)
- Corresponding author
- Gao, Shenghua
- ORCID
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2020
- Pages
- 360-377
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W3108975592
- Cited by
- 146
- References
- 43
- Citations by year
- 2026: 8 · 2025: 27 · 2024: 32 · 2023: 23 · 2022: 31 · 2021: 22 · 2020: 3
- FWCI
- 21.62
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Natural Science Foundation of China (#61932020, 2020B121201001, 2018AAA0100704)
- ShanghaiTech University
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Retinal Imaging and Analysis
- Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
- Keywords
- fundus images, optical coherence tomography, structure extraction, image reconstruction, retinal disease detection, novel class discovery, P-NET
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