Papers One-class classifier
“One-class classifier” 태그가 달린 논문 82편 · 필터 해제
Cutting Through the Noise: An Empirical Comparison of Psychoacoustic and Envelope-based Features for Machinery Fault Detection
Acoustic-based fault detection has a high potential to monitor the health condition of mechanical parts. However, the background noise of an industrial environment may negatively influence the performance of fault detect…
Fault DetectionOne-class classifierOne-Class Risk Estimation for One-Class Hyperspectral Image Classification
Hyperspectral imagery (HSI) one-class classification is aimed at identifying a single target class from the HSI by using only knowing positive data, which can significantly reduce the requirements for annotation. However…
ClassificationDeep LearningHyperspectral Image Classificationimage-classification+4Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection
Time series anomaly detection is instrumental in maintaining system availability in various domains. Current work in this research line mainly focuses on learning data normality deeply and comprehensively by devising adv…
Anomaly DetectionOne-Class ClassificationOne-class classifierTime Series+2Near out-of-distribution detection for low-resolution radar micro-Doppler signatures
Near out-of-distribution detection (OODD) aims at discriminating semantically similar data points without the supervision required for classification. This paper puts forward an OODD use case for radar targets detection …
Contrastive LearningGeometry-aware processingOne-class classifierOut-of-Distribution Detection+2OCFormer: One-Class Transformer Network for Image Classification
We propose a novel deep learning framework based on Vision Transformers (ViT) for one-class classification. The core idea is to use zero-centered Gaussian noise as a pseudo-negative class for latent space representation …
Classificationimage-classificationImage ClassificationOne-Class Classification+1SIFT and SURF based feature extraction for the anomaly detection
In this paper, we suggest a way, how to use SIFT and SURF algorithms to extract the image features for anomaly detection. We use those feature vectors to train various classifiers on a real-world dataset in the semi -sup…
Anomaly DetectionOne-class classifierMulti-class versus One-class classifier in spontaneous speech analysis oriented to Alzheimer Disease diagnosis
Most of medical developments require the ability to identify samples that are anomalous with respect to a target group or control group, in the sense they could belong to a new, previously unseen class or are not class d…
One-Class ClassificationOne-class classifierTraining a Bidirectional GAN-based One-Class Classifier for Network Intrusion Detection
The network intrusion detection task is challenging because of the imbalanced and unlabeled nature of the dataset it operates on. Existing generative adversarial networks (GANs), are primarily used for creating synthetic…
Anomaly DetectionIntrusion DetectionNetwork Intrusion DetectionOne-class classifierExemplar-free Class Incremental Learning via Discriminative and Comparable One-class Classifiers
The exemplar-free class incremental learning requires classification models to learn new class knowledge incrementally without retaining any old samples. Recently, the framework based on parallel one-class classifiers (P…
class-incremental learningClass Incremental LearningExemplar-FreeExemplar-Free Counting+2Flow-based SVDD for anomaly detection
We propose FlowSVDD -- a flow-based one-class classifier for anomaly/outliers detection that realizes a well-known SVDD principle using deep learning tools. Contrary to other approaches to deep SVDD, the proposed model i…
Anomaly DetectionOne-class classifierSelf-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection
Anomaly detection (AD), separating anomalies from normal data, has many applications across domains, from security to healthcare. While most previous works were shown to be effective for cases with fully or partially lab…
Anomaly DetectionClassificationOne-Class ClassificationOne-class classifier+2Shell Theory: A Statistical Model of Reality
The foundational assumption of machine learning is that the data under consideration is separable into classes; while intuitively reasonable, separability constraints have proven remarkably difficult to formulate mathema…
Anomaly DetectionBIG-bench Machine LearningmodelOne-class classifier+5CutPaste: Self-Supervised Learning for Anomaly Detection and Localization
We aim at constructing a high performance model for defect detection that detects unknown anomalous patterns of an image without anomalous data. To this end, we propose a two-stage framework for building anomaly detector…
Anomaly ClassificationAnomaly DetectionData AugmentationDefect Detection+4The Deep Radial Basis Function Data Descriptor (D-RBFDD) Network: A One-Class Neural Network for Anomaly Detection
Anomaly detection is a challenging problem in machine learning, and is even more so when dealing with instances that are captured in low-level, raw data representations without a well-behaved set of engineered features. …
Anomaly Detectionimage-classificationImage ClassificationOne-class classifier+1One-class Classification Robust to Geometric Transformation
Recent studies on one-class classification have achieved a remarkable performance, by employing the self-supervised classifier that predicts the geometric transformation applied to in-class images. However, they cannot i…
ClassificationGeneral ClassificationOne-Class ClassificationOne-class classifierLearning and Evaluating Representations for Deep One-class Classification
We present a two-stage framework for deep one-class classification. We first learn self-supervised representations from one-class data, and then build one-class classifiers on learned representations. The framework not o…
Anomaly DetectionClassificationContrastive LearningData Augmentation+5OneFlow: One-class flow for anomaly detection based on a minimal volume region
We propose OneFlow - a flow-based one-class classifier for anomaly (outlier) detection that finds a minimal volume bounding region. Contrary to density-based methods, OneFlow is constructed in such a way that its result …
Anomaly DetectionOne-class classifierOutlier DetectionAn ensemble of Density based Geometric One-Class Classifier and Genetic Algorithm
One of the most rising issues in recent machine learning research is One-Class Classification which considers data set composed of only one class and outliers. It is more reasonable than traditional Multi-Class Classific…
ClassificationGeneral ClassificationMulti-class ClassificationOne-Class Classification+1ADIC: Anomaly Detection Integrated Circuit in 65nm CMOS utilizing Approximate Computing
In this paper, we present a low-power anomaly detection integrated circuit (ADIC) based on a one-class classifier (OCC) neural network. The ADIC achieves low-power operation through a combination of (a) careful choice of…
Anomaly DetectionOne-class classifierARCADe: A Rapid Continual Anomaly Detector
Although continual learning and anomaly detection have separately been well-studied in previous works, their intersection remains rather unexplored. The present work addresses a learning scenario where a model has to inc…
Anomaly Detectioncontinual anomaly detectionContinual LearningMeta-Learning+1