SOTAVerified

Anomaly Detection

Anomaly Detection is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation.

[Image source]: GAN-based Anomaly Detection in Imbalance Problems

Papers

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Showing 4251–4300 of 4856 papers

TitleStatusHype
Sequential online prediction in the presence of outliers and change points: an instant temporal structure learning approach—0
ALFA: A Dataset for UAV Fault and Anomaly DetectionCode0
Towards Robust Voice Pathology Detection—0
AMAD: Adversarial Multiscale Anomaly Detection on High-Dimensional and Time-Evolving Categorical Data—0
Automated Real-time Anomaly Detection in Human Trajectories using Sequence to Sequence Networks—0
FortuneTeller: Predicting Microarchitectural Attacks via Unsupervised Deep Learning—0
Statistical Analysis of Nearest Neighbor Methods for Anomaly DetectionCode0
Interpretable Feature Learning in Multivariate Big Data Analysis for Network Monitoring—0
VELC: A New Variational AutoEncoder Based Model for Time Series Anomaly DetectionCode0
Unsupervised Anomalous Trajectory Detection for Crowded Scenes—0
Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on TextCode0
Anomaly Subsequence Detection with Dynamic Local Density for Time Series—0
An Improvement of PAA on Trend-Based Approximation for Time Series—0
Deep Multi-Task Learning for Anomalous Driving Detection Using CAN Bus Scalar Sensor Data—0
Using Self-Supervised Learning Can Improve Model Robustness and UncertaintyCode0
Detection and Statistical Modeling of Birth-Death Anomaly—0
Multivariate Big Data Analysis for Intrusion Detection: 5 steps from the haystack to the needle—0
A Survey on GANs for Anomaly DetectionCode0
AddGraph_ Anomaly Detection in Dynamic Graph Using Attention-based Temporal GCN—0
Long Short-Term Memory Neural Networks for False Information Attack Detection in Software-Defined In-Vehicle Network—0
Normalizing flows for novelty detection in industrial time series data—0
Three-Dimensional Fourier Scattering Transform and Classification of Hyperspectral ImagesCode0
Anomaly Detection with Joint Representation Learning of Content and Connection—0
GAN-based Multiple Adjacent Brain MRI Slice Reconstruction for Unsupervised Alzheimer's Disease Diagnosis—0
Stochastic Proximal AUC Maximization—0
(1 + )-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data SetsCode0
Anomaly Detection with HMM Gauge Likelihood Analysis—0
GluonTS: Probabilistic Time Series Models in PythonCode3
Warping Resilient Scalable Anomaly Detection in Time Series—0
Challenges in Time-Stamp Aware Anomaly Detection in Traffic Videos—0
Deep Learning for Spatio-Temporal Data Mining: A Survey—0
Anomaly Detection in High Performance Computers: A Vicinity Perspective—0
Time-Series Anomaly Detection Service at MicrosoftCode1
RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend FilteringCode0
Outlier Exposure with Confidence Control for Out-of-Distribution DetectionCode0
A Combination of Temporal Sequence Learning and Data Description for Anomaly-based NIDS—0
Deep Semi-Supervised Anomaly DetectionCode0
Using anomaly detection to support classification of fast running (packaging) processes—0
An Adaptive Training-less System for Anomaly Detection in Crowd Scenes—0
Detecting Anomalies in Image Classification by Means of Semantic RelationshipsCode0
MVTec AD -- A Comprehensive Real-World Dataset for Unsupervised Anomaly DetectionCode1
ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous FeaturesCode0
Time Series Anomaly Detection Using Convolutional Neural Networks and Transfer Learning—0
Bayesian Anomaly Detection Using Extreme Value Theory—0
Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT—0
Learning Temporal Causal Sequence Relationships from Real-Time Time-Series—0
Evaluation of Machine Learning-based Anomaly Detection Algorithms on an Industrial Modbus/TCP Data Set—0
Unsupervised Learning of Anomaly Detection from Contaminated Image Data using Simultaneous Encoder TrainingCode0
PNUNet: Anomaly Detection using Positive-and-Negative Noise based on Self-Training Procedure—0
Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators—0
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All datasetsMVTec ADVisAMVTec LOCO ADOne-class CIFAR-10CUHK AvenueShanghaiTechFishyscapes L&FUCR Anomaly ArchiveMPDDBTADOne-class CIFAR-100UBnormal

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016—Unverified
2CPR-fast(TensorRT)FPS362—Unverified
3CPR(TensorRT)FPS130—Unverified
4GLASSDetection AUROC99.9—Unverified
5UniNetDetection AUROC99.9—Unverified
6HETMMDetection AUROC99.8—Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9DDADDetection AUROC99.8—Unverified
10PBASDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9—Unverified
5DDADDetection AUROC98.9—Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
7DiffusionADDetection AUROC98.8—Unverified
8GLASSDetection AUROC98.8—Unverified
9TransFusionDetection AUROC98.7—Unverified
10HETMMDetection AUROC98.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3—Unverified
2PSADAvg. Detection AUROC94.9—Unverified