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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 101–150 of 227 papers

TitleStatusHype
Combining Lightly-Supervised Text Classification Models for Accurate Contextual Advertising—0
Combining One-Class Classifiers via Meta-Learning—0
Conceptron: a probabilistic deep one-class classification method—0
Conical Classification For Computationally Efficient One-Class Topic Determination—0
Conical Classification For Efficient One-Class Topic Determination—0
Constrained Deep One-Class Feature Learning For Classifying Imbalanced Medical Images—0
Contextual One-Class Classification in Data Streams—0
Point Cloud Novelty Detection Based on Latent Representations of a General Feature Extractor—0
Policy Entropy for Out-of-Distribution Classification—0
Probabilistic Saliency Estimation—0
ProtoFL: Unsupervised Federated Learning via Prototypical Distillation—0
PseudoBound: Limiting the anomaly reconstruction capability of one-class classifiers using pseudo anomalies—0
Quality assurance of organs-at-risk delineation in radiotherapy—0
Refining Myocardial Infarction Detection: A Novel Multi-Modal Composite Kernel Strategy in One-Class Classification—0
Relationship between Variants of One-Class Nearest Neighbours and Creating their Accurate Ensembles—0
[Reproducibility Report] Explainable Deep One-Class Classification—0
Restricted Generative Projection for One-Class Classification and Anomaly Detection—0
Robust Classification of High-Dimensional Spectroscopy Data Using Deep Learning and Data Synthesis—0
Robust One-Class Kernel Spectral Regression—0
SAFE-OCC: A Novelty Detection Framework for Convolutional Neural Network Sensors and its Application in Process Control—0
Score Combining for Contrastive OOD Detection—0
SD-MAD: Sign-Driven Few-shot Multi-Anomaly Detection in Medical Images—0
Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection—0
Semi-supervised Outlier Detection using Generative And Adversary Framework—0
Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification—0
SLSG: Industrial Image Anomaly Detection by Learning Better Feature Embeddings and One-Class Classification—0
Statistical and Machine Learning-based Decision Techniques for Physical Layer Authentication—0
STEP-GAN: A Step-by-Step Training for Multi Generator GANs with application to Cyber Security in Power Systems—0
Support Spinor Machine—0
Synthetic Pseudo Anomalies for Unsupervised Video Anomaly Detection: A Simple yet Efficient Framework based on Masked Autoencoder—0
Task-Specific Gradient Adaptation for Few-Shot One-Class Classification—0
Teacher Encoder-Student Decoder Denoising Guided Segmentation Network for Anomaly Detection—0
Timeseries Anomaly Detection using Temporal Hierarchical One-Class Network—0
Harnessing Contrastive Learning and Neural Transformation for Time Series Anomaly Detection—0
Towards Anomaly Detection in Dashcam Videos—0
Towards Fair Deep Anomaly Detection—0
Towards Targeted Change Detection with Heterogeneous Remote Sensing Images for Forest Mortality Mapping—0
Unsupervised Transfer Learning for Anomaly Detection: Application to Complementary Operating Condition Transfer—0
Trustworthiness of X Users: A One-Class Classification Approach—0
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning—0
Understanding Time Series Anomaly State Detection through One-Class Classification—0
Unsupervised Artifact Detection for Whole Slide Images of Prostate Biopsies—0
Unsupervised Deep One-Class Classification with Adaptive Threshold based on Training Dynamics—0
Unsupervised Learning of the Set of Local Maxima—0
Use of in-the-wild images for anomaly detection in face anti-spoofing—0
usfAD Based Effective Unknown Attack Detection Focused IDS Framework—0
Video Anomaly Detection via Spatio-Temporal Pseudo-Anomaly Generation : A Unified Approach—0
OCKELM+: Kernel Extreme Learning Machine based One-class Classification using Privileged Information (or KOC+: Kernel Ridge Regression or Least Square SVM with zero bias based One-class Classification using Privileged Information)—0
Learning Off-Road Terrain Traversability with Self-Supervisions Only—0
Learning Polynomial Representations of Physical Objects with Application to Certifying Correct Packing Configurations—0
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