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 47514800 of 4856 papers

TitleStatusHype
Histogram- and Diffusion-Based Medical Out-of-Distribution Detection0
History-based Anomaly Detector: an Adversarial Approach to Anomaly Detection0
HLogformer: A Hierarchical Transformer for Representing Log Data0
HLSAD: Hodge Laplacian-based Simplicial Anomaly Detection0
Hoi2Anomaly: An Explainable Anomaly Detection Approach Guided by Human-Object Interaction0
Holistic Features For Real-Time Crowd Behaviour Anomaly Detection0
Holmes: An Efficient and Lightweight Semantic Based Anomalous Email Detector0
HomographyAD: Deep Anomaly Detection Using Self Homography Learning0
Host-based anomaly detection using Eigentraces feature extraction and one-class classification on system call trace data0
How Far Should We Look Back to Achieve Effective Real-Time Time-Series Anomaly Detection?0
How Low Can You Go? Surfacing Prototypical In-Distribution Samples for Unsupervised Anomaly Detection0
How to boost autoencoders?0
HR-Crime: Human-Related Anomaly Detection in Surveillance Videos0
HTTP2vec: Embedding of HTTP Requests for Detection of Anomalous Traffic0
Human Abnormality Detection Based on Bengali Text0
Human-AI communication for human-human communication: Applying interpretable unsupervised anomaly detection to executive coaching0
Human-Free Automated Prompting for Vision-Language Anomaly Detection: Prompt Optimization with Meta-guiding Prompt Scheme0
Human readable network troubleshooting based on anomaly detection and feature scoring0
Human-Scene Network: A Novel Baseline with Self-rectifying Loss for Weakly supervised Video Anomaly Detection0
HURRA! Human readable router anomaly detection0
Hybrid AI-based Anomaly Detection Model using Phasor Measurement Unit Data0
Hybrid Architecture for Real-Time Video Anomaly Detection: Integrating Spatial and Temporal Analysis0
Hybrid Attention Networks for Flow and Pressure Forecasting in Water Distribution Systems0
Hybrid Cloud-Edge Collaborative Data Anomaly Detection in Industrial Sensor Networks0
Hybrid Cryptocurrency Pump and Dump Detection0
Hybrid data-driven physics model-based framework for enhance cyber-physical smart grid security0
Hybrid Deep Learning Model using SPCAGAN Augmentation for Insider Threat Analysis0
Hybrid Efficient Unsupervised Anomaly Detection for Early Pandemic Case Identification0
Hybridization of Capsule and LSTM Networks for unsupervised anomaly detection on multivariate data0
Hybrid Meta-Learning Framework for Anomaly Forecasting in Nonlinear Dynamical Systems via Physics-Inspired Simulation and Deep Ensembles0
Hybrid Model for Anomaly Detection on Call Detail Records by Time Series Forecasting0
Hybrid Temporal Differential Consistency Autoencoder for Efficient and Sustainable Anomaly Detection in Cyber-Physical Systems0
Hybrid Video Anomaly Detection for Anomalous Scenarios in Autonomous Driving0
Hyperbolic Anomaly Detection0
Hyperbolic embedding of brain networks detects regions disrupted by neurodegeneration in Alzheimer's disease0
Hyperbolic Self-supervised Contrastive Learning Based Network Anomaly Detection0
Hypergraph-based multi-scale spatio-temporal graph convolution network for Time-Series anomaly detection0
Hypergraph Learning based Recommender System for Anomaly Detection, Control and Optimization0
Hyperspectral Anomaly Detection Methods: A Survey and Comparative Study0
Hyperspectral Anomaly Detection with Self-Supervised Anomaly Prior0
iADCPS: Time Series Anomaly Detection for Evolving Cyber-physical Systems via Incremental Meta-learning0
ID-Conditioned Auto-Encoder for Unsupervised Anomaly Detection0
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection0
Identification and Characterization for Disruptions in the U.S. National Airspace System (NAS)0
Identification of Abnormality in Maize Plants From UAV Images Using Deep Learning Approaches0
Identification of temporal transition of functional states using recurrent neural networks from functional MRI0
Ignoring Distractors in the Absence of Labels: Optimal Linear Projection to Remove False Positives During Anomaly Detection0
IGRF-RFE: A Hybrid Feature Selection Method for MLP-based Network Intrusion Detection on UNSW-NB15 Dataset0
IMAFD: An Interpretable Multi-stage Approach to Flood Detection from time series Multispectral Data0
Image Anomalies: a Review and Synthesis of Detection Methods0
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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