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One-Class Classification

One-class classification (OCC) algorithms serve a crucial role in scenarios where the negative class is either absent, poorly sampled, or not well defined. This unique situation presents a challenge for building effective classifiers, as they must delineate the class boundary solely based on knowledge of the positive class. OCC has found application in various research domains, including outlier/novelty detection and concept learning.

In the context of anomaly detection, OCC models are trained exclusively on "normal" data and are subsequently tasked with identifying anomalous patterns during inference.

A one-class classifier aims at capturing characteristics of training instances, in order to be able to distinguish between them and potential outliers to appear.

— Page 139, Learning from Imbalanced Data Sets, 2018.

Papers

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Showing 51–100 of 227 papers

TitleStatusHype
Quality assurance of organs-at-risk delineation in radiotherapy—0
One-Class Classification as GLRT for Jamming Detection in Private 5G Networks—0
Critical Review for One-class Classification: recent advances and the reality behind them—0
Hyp-OC: Hyperbolic One Class Classification for Face Anti-Spoofing—0
LLM meets Vision-Language Models for Zero-Shot One-Class Classification—0
A Dual-Tier Adaptive One-Class Classification IDS for Emerging Cyberthreats—0
usfAD Based Effective Unknown Attack Detection Focused IDS Framework—0
Refining Myocardial Infarction Detection: A Novel Multi-Modal Composite Kernel Strategy in One-Class Classification—0
Trustworthiness of X Users: A One-Class Classification Approach—0
Understanding Time Series Anomaly State Detection through One-Class Classification—0
Lp-Norm Constrained One-Class Classifier Combination—0
Advancing Image Retrieval with Few-Shot Learning and Relevance FeedbackCode0
Learning Polynomial Representations of Physical Objects with Application to Certifying Correct Packing Configurations—0
OCGEC: One-class Graph Embedding Classification for DNN Backdoor DetectionCode0
Video Anomaly Detection via Spatio-Temporal Pseudo-Anomaly Generation : A Unified Approach—0
Enhancing Sentiment Analysis Results through Outlier Detection Optimization—0
Interpretable pap smear cell representation for cervical cancer screening—0
Deep Learning Predicts Biomarker Status and Discovers Related Histomorphology Characteristics for Low-Grade Glioma—0
Efficient Training of One Class Classification-SVMs—0
Credit Card Fraud Detection with Subspace Learning-based One-Class Classification—0
Newton Method-based Subspace Support Vector Data Description—0
Convolutional autoencoder-based multimodal one-class classification—0
One-Class Classification for Intrusion Detection on Vehicular Networks—0
Active anomaly detection based on deep one-class classification—0
An Iterative Method for Unsupervised Robust Anomaly Detection Under Data Contamination—0
A Perceptron-based Fine Approximation Technique for Linear Separation—0
CA2: Class-Agnostic Adaptive Feature Adaptation for One-class ClassificationCode0
Anomaly detection with semi-supervised classification based on risk estimators—0
Exploring the Optimization Objective of One-Class Classification for Anomaly Detection—0
AMAE: Adaptation of Pre-Trained Masked Autoencoder for Dual-Distribution Anomaly Detection in Chest X-Rays—0
ProtoFL: Unsupervised Federated Learning via Prototypical Distillation—0
Image Outlier Detection Without Training using RANSACCode0
LBL: Logarithmic Barrier Loss Function for One-class ClassificationCode0
Restricted Generative Projection for One-Class Classification and Anomaly Detection—0
UNTAG: LEARNING GENERIC FEATURES FOR UNSUPERVISED TYPE-AGNOSTIC DEEPFAKE DETECTIONCode0
Learning Off-Road Terrain Traversability with Self-Supervisions Only—0
Wooden Sleeper Deterioration Detection for Rural Railway Prognostics Using Unsupervised Deeper FCDDs—0
SLSG: Industrial Image Anomaly Detection by Learning Better Feature Embeddings and One-Class Classification—0
Hyperspectral Image Analysis with Subspace Learning-based One-Class Classification—0
Harnessing Contrastive Learning and Neural Transformation for Time Series Anomaly Detection—0
PseudoBound: Limiting the anomaly reconstruction capability of one-class classifiers using pseudo anomalies—0
Synthetic Pseudo Anomalies for Unsupervised Video Anomaly Detection: A Simple yet Efficient Framework based on Masked Autoencoder—0
Unsupervised Deep One-Class Classification with Adaptive Threshold based on Training Dynamics—0
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural NetworksCode0
Adapting the Hypersphere Loss Function from Anomaly Detection to Anomaly Segmentation—0
Query by example in remote sensing image archive using enhanced deep support vector data descriptionCode0
LOSDD: Leave-Out Support Vector Data Description for Outlier Detection—0
An Upper Bound for the Distribution Overlap Index and Its Applications—0
DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection—0
Chaotic Variational Auto Encoder based One Class Classifier for Insurance Fraud Detection—0
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