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 40764100 of 4856 papers

TitleStatusHype
KNN-Based Automatic Cropping for Improved Threat Object Recognition in X-Ray Security Images0
A general anomaly detection framework for fleet-based condition monitoring of machines0
History-based Anomaly Detector: an Adversarial Approach to Anomaly Detection0
Graph Embedded Pose Clustering for Anomaly DetectionCode0
Unsupervised Representation Learning by Predicting Random DistancesCode0
AEGR: A simple approach to gradient reversal in autoencoders for network anomaly detection0
Data Augmentation by AutoEncoders for Unsupervised Anomaly Detection0
NFAD: Fixing anomaly detection using normalizing flowsCode0
Unsupervised Anomaly Detection in Stream Data with Online Evolving Spiking Neural Networks0
Probabilistic Software Modeling: A Data-driven Paradigm for Software Analysis0
An Unsupervised Framework for Anomaly Detection in a Water Treatment System.Code0
MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking0
TopoAct: Visually Exploring the Shape of Activations in Deep LearningCode0
Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-190
Enabling Machine Learning Across Heterogeneous Sensor Networks with Graph Autoencoders0
Event Detection in Micro-PMU Data: A Generative Adversarial Network Scoring Method0
Peek Inside the Closed World: Evaluating Autoencoder-Based Detection of DDoS to Cloud0
Oversampling Log Messages Using a Sequence Generative Adversarial Network for Anomaly Detection and Classification0
Deep Autoencoders with Value-at-Risk Thresholding for Unsupervised Anomaly Detection0
SaLite : A light-weight model for salient object detectionCode0
PIDForest: Anomaly Detection via Partial IdentificationCode0
Transfer Learning from an Auxiliary Discriminative Task for Unsupervised Anomaly Detection0
ADEPOS: A Novel Approximate Computing Framework for Anomaly Detection Systems and its Implementation in 65nm CMOS0
Copula-based anomaly scoring and localization for large-scale, high-dimensional continuous data0
GeoTrackNet-A Maritime Anomaly Detector using Probabilistic Neural Network Representation of AIS Tracks and A Contrario DetectionCode0
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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