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Semi-supervised Anomaly Detection

Papers

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Showing 1–50 of 76 papers

TitleStatusHype
Bridging Unsupervised and Semi-Supervised Anomaly Detection: A Theoretically-Grounded and Practical Framework with Synthetic Anomalies—0
Enhanced semi-supervised stamping process monitoring with physically-informed feature extraction—0
Automated Processing of eXplainable Artificial Intelligence Outputs in Deep Learning Models for Fault Diagnostics of Large Infrastructures—0
Semi-supervised Anomaly Detection with Extremely Limited Labels in Dynamic Graphs—0
BadSAD: Clean-Label Backdoor Attacks against Deep Semi-Supervised Anomaly Detection—0
Deep evolving semi-supervised anomaly detection—0
PATH: A Discrete-sequence Dataset for Evaluating Online Unsupervised Anomaly Detection Approaches for Multivariate Time SeriesCode0
SADDE: Semi-supervised Anomaly Detection with Dependable ExplanationsCode0
Directional anomaly detection—0
Efficient Quantum One-Class Support Vector Machines for Anomaly Detection Using Randomized Measurements and Variable Subsampling—0
Infinite-dimensional Mahalanobis Distance with Applications to Kernelized Novelty DetectionCode0
Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled DataCode0
Spatial-aware Attention Generative Adversarial Network for Semi-supervised Anomaly Detection in Medical ImageCode1
Semi-supervised Anomaly Detection via Adaptive Reinforcement Learning-Enabled Method with Causal Inference for Sensor SignalsCode0
MAPL: Memory Augmentation and Pseudo-Labeling for Semi-Supervised Anomaly DetectionCode0
Machine learning-based identification of Gaia astrometric exoplanet orbitsCode0
Improving Interpretability of Scores in Anomaly Detection Based on Gaussian-Bernoulli Restricted Boltzmann Machine—0
Semi-Supervised Health Index Monitoring with Feature Generation and Fusion—0
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly GenerationCode1
Deep Semi-Supervised Anomaly Detection for Finding Fraud in the Futures Market—0
Label-based Graph Augmentation with Metapath for Graph Anomaly DetectionCode0
Semi-Supervised Anomaly Detection for the Determination of Vehicle Hijacking Tweets—0
ImbSAM: A Closer Look at Sharpness-Aware Minimization in Class-Imbalanced RecognitionCode1
Future Video Prediction from a Single Frame for Video Anomaly Detection—0
RoSAS: Deep Semi-Supervised Anomaly Detection with Contamination-Resilient Continuous SupervisionCode1
AnoOnly: Semi-Supervised Anomaly Detection with the Only Loss on AnomaliesCode0
On Diffusion Modeling for Anomaly DetectionCode1
AnoRand: A Semi Supervised Deep Learning Anomaly Detection Method by Random Labeling—0
SAD: Semi-Supervised Anomaly Detection on Dynamic GraphsCode1
Reconstruction Error-based Anomaly Detection with Few Outlying Examples—0
AGAD: Adversarial Generative Anomaly Detection—0
Zero-shot domain adaptation of anomalous samples for semi-supervised anomaly detection—0
Disruption Precursor Onset Time Study Based on Semi-supervised Anomaly Detection—0
EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level LatenciesCode2
Robust Semi-Supervised Anomaly Detection via Adversarially Learned Continuous Noise Corruption—0
Leveraging Contaminated Datasets to Learn Clean-Data Distribution with Purified Generative Adversarial NetworksCode0
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch—0
HFN: Heterogeneous Feature Network for Multivariate Time Series Anomaly Detection—0
Deep Anomaly Detection and Search via Reinforcement Learning—0
Semi-Supervised Anomaly Detection Based on Quadratic Multiform Separation—0
R2-AD2: Detecting Anomalies by Analysing the Raw GradientCode0
Unseen Anomaly Detection on Networks via Multi-Hypersphere LearningCode0
Semi-supervised anomaly detection algorithm based on KL divergence (SAD-KL)—0
LesionPaste: One-Shot Anomaly Detection for Medical Images—0
Anomaly Detection in File Fragment Classification of Image File Formats—0
A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methods—0
From Unsupervised to Semi-supervised Anomaly Detection Methods for HRRP Targets—0
Elsa: Energy-based learning for semi-supervised anomaly detection—0
Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-raysCode0
Iterative weak/self-supervised classification framework for abnormal events detectionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SS-Model + WS-Model + Sultani et al.AUC0.85—Unverified
2SS-ModelAUC0.82—Unverified
3LSTM-AEAUC0.54—Unverified
4s2-VAEAUC0.54—Unverified