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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 3851–3900 of 4856 papers

TitleStatusHype
Unsupervised Video Anomaly Detection via Normalizing Flows with Implicit Latent Features—0
Reconstruct Anomaly to Normal: Adversarial Learned and Latent Vector-constrained Autoencoder for Time-series Anomaly Detection—0
Detecting Anomalies from Video-Sequences: a Novel Descriptor—0
Anomaly Detection With Conditional Variational Autoencoders—0
Anomaly Detection based on Zero-Shot Outlier Synthesis and Hierarchical Feature Distillation—0
Unsupervised 3D Brain Anomaly Detection—0
Algorithmic Frameworks for the Detection of High Density AnomaliesCode0
Anomaly detection with superexperts under delayed feedbackCode0
Deep learning models for predictive maintenance: a survey, comparison, challenges and prospect—0
Anomaly Detection in Large Labeled Multi-Graph Databases—0
Anomaly Detection Approach to Identify Early Cases in a Pandemic using Chest X-raysCode0
RANDGAN: Randomized Generative Adversarial Network for Detection of COVID-19 in Chest X-rayCode0
OneFlow: One-class flow for anomaly detection based on a minimal volume region—0
GLOSS: Tensor-Based Anomaly Detection in Spatiotemporal Urban Traffic Data—0
Video Anomaly Detection Using Pre-Trained Deep Convolutional Neural Nets and Context Mining—0
Global soil moisture from in-situ measurements using machine learning -- SoMo.ml—0
Deep Anomaly Detection by Residual Adaptation—0
Unsupervised Region-based Anomaly Detection in Brain MRI with Adversarial Image Inpainting—0
TimeAutoML: Autonomous Representation Learning for Multivariate Irregularly Sampled Time Series—0
ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed NetworksCode0
A Survey on Deep Learning Techniques for Video Anomaly Detection—0
A comparison of classical and variational autoencoders for anomaly detection—0
Anomaly Detection and Sampling Cost Control via Hierarchical GANs—0
STAN: Synthetic Network Traffic Generation with Generative Neural ModelsCode0
Deep Autoencoding GMM-based Unsupervised Anomaly Detection in Acoustic Signals and its Hyper-parameter Optimization—0
A Unifying Review of Deep and Shallow Anomaly Detection—0
Regularizing Attention Networks for Anomaly Detection in Visual Question Answering—0
Out-Of-Bag Anomaly Detection—0
Unsupervised Anomaly Detection on Temporal Multiway Data—0
A deep learning-based approach for the automated surface inspection of copper clad laminate images—0
On Multi-Session Website Fingerprinting over TLS Handshake—0
PANDA: Predicting the change in proteins binding affinity upon mutations using sequence informationCode0
Anomaly and Fraud Detection in Credit Card Transactions Using the ARIMA Model—0
Machine Learning and Data Science approach towards trend and predictors analysis of CDC Mortality Data for the USA—0
Machine Learning Applications in Misuse and Anomaly Detection—0
Label-Free Segmentation of COVID-19 Lesions in Lung CT—0
Detection of Anomalies and Faults in Industrial IoT Systems by Data Mining: Study of CHRIST Osmotron Water Purification System—0
Anomaly Detection With Partitioning Overfitting Autoencoder EnsemblesCode0
Deep Learning for the Analysis of Disruption Precursors based on Plasma Tomography—0
Towards the Development of Entropy-Based Anomaly Detection in an Astrophysics Simulation—0
Simulation-Assisted Decorrelation for Resonant Anomaly DetectionCode0
Connecting Web Event Forecasting with Anomaly Detection: A Case Study on Enterprise Web Applications Using Self-Supervised Neural Networks—0
Anomaly Detection by Recombining Gated Unsupervised ExpertsCode0
Data Anomaly Detection for Structural Health Monitoring of Bridges using Shapelet Transform—0
Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly DetectionCode0
Puzzle-AE: Novelty Detection in Images through Solving PuzzlesCode0
GAN-based Anomaly Detection in Imbalance Problems—0
A Self-Reasoning Framework for Anomaly Detection Using Video-Level Labels—0
The Impact of Discretization Method on the Detection of Six Types of Anomalies in DatasetsCode0
Training robust anomaly detection using ML-Enhanced simulations—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