Papers One-class classifier
“One-class classifier” 태그가 달린 논문 82편 · 필터 해제
Cascade of one-class classifier ensemble and dynamic naive Bayes classifier applied to the myoelectric-based upper limb prosthesis control with contaminated channels detection
Modern upper limb bioprostheses are typically controlled by sEMG signals using a pattern recognition scheme in the control process. Unfortunately, the sEMG signal is very susceptible to contamination that deteriorates th…
One-class classifierLocally Adaptive One-Class Classifier Fusion with Dynamic $\ell$p-Norm Constraints for Robust Anomaly Detection
This paper presents a novel approach to one-class classifier fusion through locally adaptive learning with dynamic $\ell$p-norm constraints. We introduce a framework that dynamically adjusts fusion weights based on local…
Anomaly DetectionComputational EfficiencyOne-class classifierFedMSE: Federated learning for IoT network intrusion detection
This paper proposes a novel federated learning approach for improving IoT network intrusion detection. The rise of IoT has expanded the cyber attack surface, making traditional centralized machine learning methods insuff…
Federated LearningIntrusion DetectionNetwork Intrusion DetectionOne-class classifierPoint Cloud Novelty Detection Based on Latent Representations of a General Feature Extractor
We propose an effective unsupervised 3D point cloud novelty detection approach, leveraging a general point cloud feature extractor and a one-class classifier. The general feature extractor consists of a graph-based autoe…
Novelty DetectionOne-Class ClassificationOne-class classifierQuality assurance of organs-at-risk delineation in radiotherapy
The delineation of tumor target and organs-at-risk is critical in the radiotherapy treatment planning. Automatic segmentation can be used to reduce the physician workload and improve the consistency. However, the quality…
One-Class ClassificationOne-class classifierSpecificityBeyond the Known: Adversarial Autoencoders in Novelty Detection
In novelty detection, the goal is to decide if a new data point should be categorized as an inlier or an outlier, given a training dataset that primarily captures the inlier distribution. Recent approaches typically use …
DecoderNovelty DetectionOne-class classifierGenerative Semi-supervised Graph Anomaly Detection
This work considers a practical semi-supervised graph anomaly detection (GAD) scenario, where part of the nodes in a graph are known to be normal, contrasting to the extensively explored unsupervised setting with a fully…
Anomaly DetectionGraph Anomaly DetectionOne-class classifierOne-class anomaly detection through color-to-thermal AI for building envelope inspection
We present a label-free method for detecting anomalies during thermographic inspection of building envelopes. It is based on the AI-driven prediction of thermal distributions from color images. Effectively the method per…
Anomaly DetectionOne-class classifierLp-Norm Constrained One-Class Classifier Combination
Classifier fusion is established as an effective methodology for boosting performance in different settings and one-class classification is no exception. In this study, we consider the one-class classifier fusion problem…
One-Class ClassificationOne-class classifierOCGEC: One-class Graph Embedding Classification for DNN Backdoor Detection
Deep neural networks (DNNs) have been found vulnerable to backdoor attacks, raising security concerns about their deployment in mission-critical applications. There are various approaches to detect backdoor attacks, howe…
Anomaly Detectionbackdoor defenseGraph EmbeddingOne-Class Classification+1Two-Factor Authentication Approach Based on Behavior Patterns for Defeating Puppet Attacks
Fingerprint traits are widely recognized for their unique qualities and security benefits. Despite their extensive use, fingerprint features can be vulnerable to puppet attacks, where attackers manipulate a reluctant but…
feature selectionOne-class classifierAn Improved Anomaly Detection Model for Automated Inspection of Power Line Insulators
Inspection of insulators is important to ensure reliable operation of the power system. Deep learning is being increasingly exploited to automate the inspection process by leveraging object detection models to analyse ae…
Anomaly DetectionFault DetectionObjectobject-detection+2ProtoFL: Unsupervised Federated Learning via Prototypical Distillation
Federated learning (FL) is a promising approach for enhancing data privacy preservation, particularly for authentication systems. However, limited round communications, scarce representation, and scalability pose signifi…
Federated LearningOne-Class ClassificationOne-class classifierMorse Neural Networks for Uncertainty Quantification
We introduce a new deep generative model useful for uncertainty quantification: the Morse neural network, which generalizes the unnormalized Gaussian densities to have modes of high-dimensional submanifolds instead of ju…
Anomaly DetectionOne-class classifierUncertainty QuantificationUNTAG: LEARNING GENERIC FEATURES FOR UNSUPERVISED TYPE-AGNOSTIC DEEPFAKE DETECTION
This paper introduces a novel framework for unsupervised type-agnostic deepfake detection called UNTAG. Existing methods are generally trained in a supervised manner at the classification level, focusing on detecting at …
DeepFake DetectionFace SwappingOne-Class ClassificationOne-class classifierA One-Class Classifier for the Detection of GAN Manipulated Multi-Spectral Satellite Images
The highly realistic image quality achieved by current image generative models has many academic and industrial applications. To limit the use of such models to benign applications, though, it is necessary that tools to …
One-class classifierDetecting Anomalous Microflows in IoT Volumetric Attacks via Dynamic Monitoring of MUD Activity
IoT networks are increasingly becoming target of sophisticated new cyber-attacks. Anomaly-based detection methods are promising in finding new attacks, but there are certain practical challenges like false-positive alarm…
One-class classifierAn Upper Bound for the Distribution Overlap Index and Its Applications
This paper proposes an easy-to-compute upper bound for the overlap index between two probability distributions without requiring any knowledge of the distribution models. The computation of our bound is time-efficient an…
ClassificationOne-Class ClassificationOne-class classifierChaotic Variational Auto Encoder based One Class Classifier for Insurance Fraud Detection
Of late, insurance fraud detection has assumed immense significance owing to the huge financial & reputational losses fraud entails and the phenomenal success of the fraud detection techniques. Insurance is majorly divid…
Fraud DetectionOne-Class ClassificationOne-class classifierDOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection
Machine Learning (ML) approaches have been used to enhance the detection capabilities of Network Intrusion Detection Systems (NIDSs). Recent work has achieved near-perfect performance by following binary- and multi-class…
Anomaly DetectionIntrusion DetectionNetwork Intrusion DetectionOne-Class Classification+2