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

Showing 34513500 of 4856 papers

TitleStatusHype
TIMo -- A Dataset for Indoor Building Monitoring with a Time-of-Flight Camera0
Anomaly Detection on IT Operation Series via Online Matrix Profile0
End-To-End Anomaly Detection for Identifying Malicious Cyber Behavior through NLP-Based Log Embeddings0
Human readable network troubleshooting based on anomaly detection and feature scoring0
DeepFlow: Abnormal Traffic Flow Detection Using Siamese Networks0
Anomaly Detection in Medical Imaging -- A Mini Review0
Weakly-supervised Joint Anomaly Detection and Classification0
CloudShield: Real-time Anomaly Detection in the CloudCode0
Abnormal Road Surface Detection Using Wheel Sensor Data0
Federated Variational Learning for Anomaly Detection in Multivariate Time Series0
Event2Graph: Event-driven Bipartite Graph for Multivariate Time-series Anomaly Detection0
Random Subspace Mixture Models for Interpretable Anomaly Detection0
Unconditional Scene Graph Generation0
Unsupervised Driver Behavior Profiling leveraging Recurrent Neural Networks0
CPNet: Cross-Parallel Network for Efficient Anomaly DetectionCode0
Flow-based SVDD for anomaly detection0
Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video0
Transfer Learning Gaussian Anomaly Detection by Fine-tuning Representations0
Scaling New Peaks: A Viewership-centric Approach to Automated Content Curation0
Anomaly Detection Based on Generalized Gaussian Distribution approach for Ultra-Wideband (UWB) Indoor Positioning System0
Adaptive Anomaly Detection for Internet of Things in Hierarchical Edge Computing: A Contextual-Bandit Approach0
Ensemble neuroevolution based approach for multivariate time series anomaly detection0
Locally Interpretable One-Class Anomaly Detection for Credit Card Fraud DetectionCode0
Using a Collated Cybersecurity Dataset for Machine Learning and Artificial Intelligence0
Deep Anomaly Discovery From Unlabeled Videos via Normality Advantage and Self-Paced Refinement0
Unsupervised Detection of Lung Nodules in Chest Radiography Using Generative Adversarial Networks0
HTTP2vec: Embedding of HTTP Requests for Detection of Anomalous Traffic0
Efficacy of Statistical and Artificial Intelligence-based False Information Cyberattack Detection Models for Connected Vehicles0
HR-Crime: Human-Related Anomaly Detection in Surveillance Videos0
Margin-Aware Intra-Class Novelty Identification for Medical ImagesCode0
Anomaly Detection with Neural Parsers That Never Reject0
Using Visual Anomaly Detection for Task Execution MonitoringCode0
Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection0
Underwater Acoustic Networks for Security Risk Assessment in Public Drinking Water Reservoirs0
Fast Wireless Sensor Anomaly Detection based on Data Stream in Edge Computing Enabled Smart Greenhouse0
Divide-and-Assemble: Learning Block-wise Memory for Unsupervised Anomaly Detection0
Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals0
Source-Agnostic Gravitational-Wave Detection with Recurrent Autoencoders0
Discriminative-Generative Representation Learning for One-Class Anomaly Detection0
Multi-Perspective Content Delivery Networks Security Framework Using Optimized Unsupervised Anomaly Detection0
Tail of Distribution GAN (TailGAN): Generative-Adversarial-Network-Based Boundary Formation0
HURRA! Human readable router anomaly detection0
Integrating Deep Learning and Augmented Reality to Enhance Situational Awareness in Firefighting Environments0
Anomaly Detection via Self-organizing MapCode0
Boundary of Distribution Support Generator (BDSG): Sample Generation on the Boundary0
A Comparison of Supervised and Unsupervised Deep Learning Methods for Anomaly Detection in ImagesCode0
Canonical Polyadic Decomposition and Deep Learning for Machine Fault Detection0
Image-Hashing-Based Anomaly Detection for Privacy-Preserving Online Proctoring0
OnlineSTL: Scaling Time Series Decomposition by 100x0
Explainable Debugger for Black-box Machine Learning ModelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016Unverified
2CPR-fast(TensorRT)FPS362Unverified
3CPR(TensorRT)FPS130Unverified
4GLASSDetection AUROC99.9Unverified
5UniNetDetection AUROC99.9Unverified
6HETMMDetection AUROC99.8Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8Unverified
8EfficientAD (early stopping)Detection AUROC99.8Unverified
9DDADDetection AUROC99.8Unverified
10PBASDetection AUROC99.8Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8Unverified
2GLADDetection AUROC99.5Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9Unverified
5DDADDetection AUROC98.9Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9Unverified
7DiffusionADDetection AUROC98.8Unverified
8GLASSDetection AUROC98.8Unverified
9TransFusionDetection AUROC98.7Unverified
10HETMMDetection AUROC98.1Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3Unverified
2PSADAvg. Detection AUROC94.9Unverified