October 01, 2019 conference-paper Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection IEEE/CVF International Conference on Computer Vision (ICCV) DOI: 10.1109/iccv.2019.00179 OpenAlex Authors 0 Author list not loaded yet. Cited by 3 stored of 1,758 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection 2021 Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition conference-paper Computer Science Anomaly Detection Techniques and Applications Open access cited by 5 patents 261 citations Autoencoders for unsupervised anomaly detection in high energy physics 2021 RWTH Publications (RWTH Aachen) article Physics and Astronomy Particle physics theoretical and experimental studies Open access 100 citations Gaussian Anomaly Detection by Modeling the Distribution of Normal Data in Pretrained Deep Features 2021 IEEE Transactions on Instrumentation and Measurement article Computer Science Anomaly Detection Techniques and Applications Open access cited by 2 patents 85 citations 3 results References 0