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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 51–100 of 155 papers

TitleStatusHype
An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videosCode0
Confidence-Aware and Self-Supervised Image Anomaly LocalisationCode0
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 AI System for Continuous Knee Osteoarthritis Severity Grading Using Self-Supervised Anomaly Detection with Limited DataCode0
A One-Class Classification method based on Expanded Non-Convex HullsCode0
SADDE: Semi-supervised Anomaly Detection with Dependable ExplanationsCode0
Deep Weakly-supervised Anomaly DetectionCode0
AnoOnly: Semi-Supervised Anomaly Detection with the Only Loss on AnomaliesCode0
GANomaly: Semi-Supervised Anomaly Detection via Adversarial TrainingCode0
Self-Supervised Anomaly Detection by Self-Distillation and Negative SamplingCode0
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly DetectionCode0
Graph Fairing Convolutional Networks for Anomaly DetectionCode0
A Comparison of Supervised and Unsupervised Deep Learning Methods for Anomaly Detection in ImagesCode0
Understanding Bias in Anomaly Detection: A Semi-Supervised View with PAC GuaranteesCode0
Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-raysCode0
Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled DataCode0
Semi-supervised anomaly detection algorithm based on KL divergence (SAD-KL)—0
Semi-Supervised Anomaly Detection Based on Quadratic Multiform Separation—0
Semi-Supervised Anomaly Detection for the Determination of Vehicle Hijacking Tweets—0
Semi-supervised Anomaly Detection with Extremely Limited Labels in Dynamic Graphs—0
Semi-Supervised Health Index Monitoring with Feature Generation and Fusion—0
Semi-supervised learning via DQN for log anomaly detection—0
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
Zero-shot domain adaptation of anomalous samples for semi-supervised anomaly detection—0
Abuse and Fraud Detection in Streaming Services Using Heuristic-Aware Machine Learning—0
A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methods—0
Adaptive Graph Convolutional Networks for Weakly Supervised Anomaly Detection in Videos—0
AGAD: Adversarial Generative Anomaly Detection—0
A Neural Network-Based On-device Learning Anomaly Detector for Edge Devices—0
Anomaly Detection by Context Contrasting—0
Anomaly Detection for an E-commerce Pricing System—0
Anomaly Detection in Electrocardiograms: Advancing Clinical Diagnosis Through Self-Supervised Learning—0
Anomaly Detection in File Fragment Classification of Image File Formats—0
Anomaly Detection with Domain Adaptation—0
Anomaly Detection with Inexact Labels—0
AnoNet: Weakly Supervised Anomaly Detection in Textured Surfaces—0
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