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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 101–150 of 155 papers

TitleStatusHype
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch—0
Supervised Anomaly Detection based on Deep Autoregressive Density Estimators—0
Supervised Anomaly Detection in Uncertain Pseudoperiodic Data Streams—0
Supervised Anomaly Detection Method Combining Generative Adversarial Networks and Three-Dimensional Data in Vehicle Inspections—0
Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization—0
Toward Supervised Anomaly Detection—0
Unsupervised and Semi-supervised Anomaly Detection with LSTM Neural Networks—0
Using Channel State Information for Physical Tamper Attack Detection in OFDM Systems: A Deep Learning Approach—0
Weakly-supervised anomaly detection for multimodal data distributions—0
Weakly-Supervised Anomaly Detection in Surveillance Videos Based on Two-Stream I3D Convolution Network—0
Weakly Supervised Anomaly Detection via Knowledge-Data Alignment—0
Weakly Supervised Detection of Baby Cry—0
Anomaly Detection in Images—0
LesionPaste: One-Shot Anomaly Detection for Medical Images—0
Locality-aware Attention Network with Discriminative Dynamics Learning for Weakly Supervised Anomaly Detection—0
LogELECTRA: Self-supervised Anomaly Detection for Unstructured Logs—0
Look Around for Anomalies: Weakly-Supervised Anomaly Detection via Context-Motion Relational Learning—0
IgCONDA-PET: Weakly-Supervised PET Anomaly Detection using Implicitly-Guided Attention-Conditional Counterfactual Diffusion Modeling -- a Multi-Center, Multi-Cancer, and Multi-Tracer StudyCode0
Label-based Graph Augmentation with Metapath for Graph Anomaly DetectionCode0
Leveraging Contaminated Datasets to Learn Clean-Data Distribution with Purified Generative Adversarial NetworksCode0
Deep Semi-Supervised Anomaly DetectionCode0
Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-raysCode0
An AI System for Continuous Knee Osteoarthritis Severity Grading Using Self-Supervised Anomaly Detection with Limited DataCode0
Machine learning-based identification of Gaia astrometric exoplanet orbitsCode0
MAPL: Memory Augmentation and Pseudo-Labeling for Semi-Supervised Anomaly DetectionCode0
ADFA: Attention-augmented Differentiable top-k Feature Adaptation for Unsupervised Medical Anomaly DetectionCode0
Weakly-Supervised Video Anomaly Detection with Snippet Anomalous AttentionCode0
MTFL: Multi-Timescale Feature Learning for Weakly-Supervised Anomaly Detection in Surveillance VideosCode0
Weakly Supervised Anomaly Detection for Chest X-Ray ImageCode0
How to Evaluate the Quality of Unsupervised Anomaly Detection Algorithms?Code0
Semi-supervised Anomaly Detection on Attributed GraphsCode0
Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled DataCode0
A Characteristic Function for Shapley-Value-Based Attribution of Anomaly ScoresCode0
Hop-Count Based Self-Supervised Anomaly Detection on Attributed NetworksCode0
Semi-supervised Anomaly Detection via Adaptive Reinforcement Learning-Enabled Method with Causal Inference for Sensor SignalsCode0
Understanding Bias in Anomaly Detection: A Semi-Supervised View with PAC GuaranteesCode0
Unseen Anomaly Detection on Networks via Multi-Hypersphere LearningCode0
Graph Fairing Convolutional Networks for Anomaly DetectionCode0
Deep Weakly-supervised Anomaly DetectionCode0
Confidence-Aware and Self-Supervised Image Anomaly LocalisationCode0
R2-AD2: Detecting Anomalies by Analysing the Raw GradientCode0
PATH: A Discrete-sequence Dataset for Evaluating Online Unsupervised Anomaly Detection Approaches for Multivariate Time SeriesCode0
A One-Class Classification method based on Expanded Non-Convex HullsCode0
Multi-Normal Prototypes Learning for Weakly Supervised Anomaly DetectionCode0
Weakly-Supervised Anomaly Detection in the Milky WayCode0
Revisiting Non-separable Binary Classification and its Applications in Anomaly DetectionCode0
An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videosCode0
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly DetectionCode0
SADDE: Semi-supervised Anomaly Detection with Dependable ExplanationsCode0
GANomaly: Semi-Supervised Anomaly Detection via Adversarial TrainingCode0
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