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Supervised Anomaly Detection

In the training set, the amount of abnormal samples is limited and significant fewer than normal samples, producing data distributions that lead to a naturally imbalanced learning problem.

Papers

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Showing 76–100 of 155 papers

TitleStatusHype
SeMAnD: Self-Supervised Anomaly Detection in Multimodal Geospatial Datasets—0
Deep Semi-Supervised Anomaly Detection for Finding Fraud in the Futures Market—0
ADFA: Attention-augmented Differentiable top-k Feature Adaptation for Unsupervised Medical Anomaly DetectionCode0
Label-based Graph Augmentation with Metapath for Graph Anomaly DetectionCode0
Semi-Supervised Anomaly Detection for the Determination of Vehicle Hijacking Tweets—0
Future Video Prediction from a Single Frame for Video Anomaly Detection—0
End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection—0
Industrial Anomaly Detection and Localization Using Weakly-Supervised Residual Transformers—0
AnoOnly: Semi-Supervised Anomaly Detection with the Only Loss on AnomaliesCode0
AnoRand: A Semi Supervised Deep Learning Anomaly Detection Method by Random Labeling—0
Reconstruction Error-based Anomaly Detection with Few Outlying Examples—0
Self-Supervised Anomaly Detection of Rogue Soil Moisture Sensors—0
Weakly-Supervised Anomaly Detection in the Milky WayCode0
Weakly Supervised Detection of Baby Cry—0
Few-shot Weakly-supervised Cybersecurity Anomaly Detection—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
Confidence-Aware and Self-Supervised Image Anomaly LocalisationCode0
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
Look Around for Anomalies: Weakly-Supervised Anomaly Detection via Context-Motion Relational Learning—0
Supervised Anomaly Detection Method Combining Generative Adversarial Networks and Three-Dimensional Data in Vehicle Inspections—0
Prototypical Residual Networks for Anomaly Detection and Localization—0
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch—0
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