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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 101–125 of 155 papers

TitleStatusHype
LesionPaste: One-Shot Anomaly Detection for Medical Images—0
Diffusion Models for Medical Anomaly DetectionCode1
Abuse and Fraud Detection in Streaming Services Using Heuristic-Aware Machine Learning—0
Anomaly Detection in File Fragment Classification of Image File Formats—0
Adaptive Graph Convolutional Networks for Weakly Supervised Anomaly Detection in Videos—0
Self-Supervised Anomaly Detection by Self-Distillation and Negative SamplingCode0
SLA^2P: Self-supervised Anomaly Detection with Adversarial PerturbationCode1
A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methods—0
Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and LocalizationCode1
No Shifted Augmentations (NSA): strong baselines for self-supervised Anomaly Detection—0
Explainable Deep Few-shot Anomaly Detection with Deviation NetworksCode1
A Comparison of Supervised and Unsupervised Deep Learning Methods for Anomaly Detection in ImagesCode0
From Unsupervised to Semi-supervised Anomaly Detection Methods for HRRP Targets—0
DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly DetectionCode1
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly DetectionCode1
Cleaning Label Noise with Clusters for Minimally Supervised Anomaly Detection—0
Supervised Anomaly Detection via Conditional Generative Adversarial Network and Ensemble Active LearningCode1
Hop-Count Based Self-Supervised Anomaly Detection on Attributed NetworksCode0
Elsa: Energy-based learning for semi-supervised anomaly detection—0
Meta-learning One-class Classifiers with Eigenvalue Solvers for Supervised Anomaly Detection—0
Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-raysCode0
Understanding Bias in Anomaly Detection: A Semi-Supervised View with PAC GuaranteesCode0
ESAD: End-to-end Deep Semi-supervised Anomaly Detection—0
CLAWS: Clustering Assisted Weakly Supervised Learning with Normalcy Suppression for Anomalous Event Detection—0
Using Channel State Information for Physical Tamper Attack Detection in OFDM Systems: A Deep Learning Approach—0
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