Papers with Code 아카이브

Anomaly Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 28
평가표: 76
보존된 평가 기록: 669

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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/nulog/nulog

공식 코드

Self-Supervised Log Parsing

https://github.com/numenta/NAB

공식 코드

Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark

https://github.com/nwpu-zxr/vadclip

공식 코드

VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly Detection

https://github.com/nxhoang56/explainable-anomaly-detection-forindustrial-control-system-cybersecurity

공식 코드

Explainable Anomaly Detection for Industrial Control System Cybersecurity

https://github.com/okankop/Driver-Anomaly-Detection

공식 코드

Driver Anomaly Detection: A Dataset and Contrastive Learning Approach

https://github.com/oliverkn/alad-for-lhc

공식 코드

Adversarially Learned Anomaly Detection on CMS Open Data: re-discovering the top quark

https://github.com/olivesgatech/gradcon-anomaly

공식 코드

Backpropagated Gradient Representations for Anomaly Detection

https://github.com/oopil/PSAD_logical_anomaly_detection

공식 코드

Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection

https://github.com/openai/glow

공식 코드

Glow: Generative Flow with Invertible 1x1 Convolutions

https://github.com/openvinotoolkit/anomalib

공식 코드

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training

https://github.com/opspai/mtad

공식 코드

MTAD: Tools and Benchmarks for Multivariate Time Series Anomaly Detection

https://github.com/oracle/tribuo

공식 코드

Tribuo: Machine Learning with Provenance in Java

https://github.com/orhir/stg-nf

공식 코드

Normalizing Flows for Human Pose Anomaly Detection

https://github.com/oskarastrom/CL-VAE

공식 코드

Improved Anomaly Detection through Conditional Latent Space VAE Ensembles

https://github.com/otkupjnoz/oc-cnn

공식 코드

One-Class Convolutional Neural Network

https://github.com/outbrain/outrank

공식 코드

OutRank: Speeding up AutoML-based Model Search for Large Sparse Data sets with Cardinality-aware Feature Ranking

https://github.com/pankajmishra000/VT-ADL

공식 코드

VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization

https://github.com/paulinebourigault/ghkernelanomalydetect

공식 코드

Kernel-Based Anomaly Detection Using Generalized Hyperbolic Processes

https://github.com/pcwhy/AbnormalityDetectionInZbDNN

공식 코드

Zero-bias Deep Learning Enabled Quick and Reliable Abnormality Detection in IoT

https://github.com/peirong26/una

공식 코드

Unraveling Normal Anatomy via Fluid-Driven Anomaly Randomization

https://github.com/phrenico/uniqed

공식 코드

How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time series

https://github.com/pinyuchen/FINGER

공식 코드

Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications

https://github.com/pipixin321/glancevad

공식 코드

GlanceVAD: Exploring Glance Supervision for Label-efficient Video Anomaly Detection

https://github.com/pipixin321/holmesvad

공식 코드

Holmes-VAD: Towards Unbiased and Explainable Video Anomaly Detection via Multi-modal LLM

https://github.com/pipixin321/holmesvau

공식 코드

Holmes-VAU: Towards Long-term Video Anomaly Understanding at Any Granularity

https://github.com/pirofti/ad-usr-dl

공식 코드

Dictionary Learning with Uniform Sparse Representations for Anomaly Detection

https://github.com/pkorus/neural-imaging

공식 코드

Content Authentication for Neural Imaging Pipelines: End-to-end Optimization of Photo Provenance in Complex Distribution Channels

https://github.com/plan-lab/mtsbench

공식 코드

mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale

https://github.com/pnnl/safekit

공식 코드

Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams

https://github.com/polimi-ispl/icpr2020dfdc

공식 코드

Video Face Manipulation Detection Through Ensemble of CNNs

https://github.com/poseidon-workflows/llm_ad

공식 코드

Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning

https://github.com/positivetechnologylab/Quorum

공식 코드

Quorum: Zero-Training Unsupervised Anomaly Detection using Quantum Autoencoders

https://github.com/prnshv/oran-bench-13k

공식 코드

ORAN-Bench-13K: An Open Source Benchmark for Assessing LLMs in Open Radio Access Networks

https://github.com/project-monai/generativemodels

공식 코드

Generative AI for Medical Imaging: extending the MONAI Framework

https://github.com/proteus1991/pscc-net

공식 코드

PSCC-Net: Progressive Spatio-Channel Correlation Network for Image Manipulation Detection and Localization

https://github.com/proy3/NLAP-net_VAD

공식 코드

Predicting Next Local Appearance for Video Anomaly Detection

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.