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Anomaly Detection

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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/zhonglifr/logs2graph

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Graph Neural Networks based Log Anomaly Detection and Explanation

https://github.com/zhonglifr/qcad

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Explainable Contextual Anomaly Detection using Quantile Regression Forests

https://github.com/zhouxr6066/Res-SAM

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Reservoir-enhanced Segment Anything Model for Subsurface Diagnosis

https://github.com/zhuergou/energy-transformer-for-graph-anomaly-detection

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Energy Transformer

https://github.com/zhuye88/CDF-TS

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CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities

https://github.com/zhyjsiat/a-two-stage-cyclegan-ve-brats2020

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A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detection

https://github.com/zichunhao/lgn-autoencoder

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Lorentz group equivariant autoencoders

https://github.com/ziyunliang/mmccd

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Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI

https://github.com/zjlab-ammi/q-net

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Q-Net: Query-Informed Few-Shot Medical Image Segmentation

https://github.com/zjs123/anot

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Online Detection of Anomalies in Temporal Knowledge Graphs with Interpretability

https://github.com/zli12321/videohallu

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VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations on Synthetic Video Understanding

https://github.com/znchen666/fico

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Filter or Compensate: Towards Invariant Representation from Distribution Shift for Anomaly Detection

https://github.com/zqhang/anomalyclip

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AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection

https://github.com/zqhang/detecting-multivariate-time-series-anomalies-with-zero-known-label

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Detecting Multivariate Time Series Anomalies with Zero Known Label

https://github.com/zqhang/mtgflow

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Detecting Multivariate Time Series Anomalies with Zero Known Label

https://github.com/zqhang/pointad

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PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection

https://github.com/zqzqz/advcollaborativeperception

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On Data Fabrication in Collaborative Vehicular Perception: Attacks and Countermeasures

https://github.com/zshhans/msd-mixer

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A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis

https://github.com/zugexiaodui/llshforvad

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Learnable Locality-Sensitive Hashing for Video Anomaly Detection

https://github.com/zugexiaodui/twostreamuvad

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Context Recovery and Knowledge Retrieval: A Novel Two-Stream Framework for Video Anomaly Detection

https://github.com/zurutech/anomaly-toolbox

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A Survey on GANs for Anomaly Detection

https://github.com/zx-pan/medanomalydetection-iqa

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Rethinking Medical Anomaly Detection in Brain MRI: An Image Quality Assessment Perspective

https://github.com/zxuandang/atd-via-flows

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Semi-Supervised Learning for Anomaly Traffic Detection via Bidirectional Normalizing Flows

https://github.com/zzr728/sagan

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Spatial-aware Attention Generative Adversarial Network for Semi-supervised Anomaly Detection in Medical Image

https://github.com/zzzbbbzzz/mulsen-ad

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Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties

https://gitlab.au.dk/maleci/audiovisualanomalydetection

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Audio-Visual Dataset and Method for Anomaly Detection in Traffic Videos

https://gitlab.com/Dmitry_Otryakhin/fast-automatic-deforestation-detection-supplementary-materials

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Automatic deforestation detectors based on frequentist statistics and their extensions for other spatial objects

https://gitlab.com/MISLgit/forensic-similarity-for-digital-images

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Forensic Similarity for Digital Images

https://gitlab.com/alessiomascolini/varade

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VARADE: a Variational-based AutoRegressive model for Anomaly Detection on the Edge

https://gitlab.com/cian.unibas.ch/diffusion-anomaly

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Diffusion Models for Medical Anomaly Detection

https://gitlab.com/cian.unibas.ch/position-regression

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Position Regression for Unsupervised Anomaly Detection

https://gitlab.com/dlr-dw/is-it-worth-it-benchmark

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Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series

https://gitlab.com/dlr-dw/unraveling-anomalies-in-time

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Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-regenerative Life Support System Telemetry

https://gitlab.com/jackaraz/qhbm

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Quantum-probabilistic Hamiltonian learning for generative modelling & anomaly detection

https://gitlab.com/lambda-hse/nfad

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NFAD: Fixing anomaly detection using normalizing flows

https://gitlab.com/mborisyak/ope

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$(1 + \varepsilon)$-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets

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