Papers One-Class Classification
“One-Class Classification” 태그가 달린 논문 227편 · 필터 해제
Multi-Task Kernel Null-Space for One-Class Classification
The one-class kernel spectral regression (OC-KSR), the regression-based formulation of the kernel null-space approach has been found to be an effective Fisher criterion-based methodology for one-class classification (OCC…
ClassificationGeneral ClassificationOne-Class ClassificationregressionA Multi-modal one-class generative adversarial network for anomaly detection in manufacturing
One class anomaly detection on high-dimensional data is one of the critical issue in both fundamental machine learning research area and manufacturing applica- tions. A good anomaly detection should accurately discrimina…
Anomaly DetectionGenerative Adversarial NetworkOne-Class ClassificationEnd-to-End Adversarial Learning for Intrusion Detection in Computer Networks
This paper presents a simple yet efficient method for an anomaly-based Intrusion Detection System (IDS). In reality, IDSs can be defined as a one-class classification system, where the normal traffic is the target class.…
DiversityIntrusion DetectionOne-Class ClassificationMultimodal Subspace Support Vector Data Description
In this paper, we propose a novel method for projecting data from multiple modalities to a new subspace optimized for one-class classification. The proposed method iteratively transforms the data from the original featur…
AllGeneral ClassificationOne-Class ClassificationGraph-Embedded Multi-layer Kernel Extreme Learning Machine for One-class Classification or (Graph-Embedded Multi-layer Kernel Ridge Regression for One-class Classification)
A brain can detect outlier just by using only normal samples. Similarly, one-class classification (OCC) also uses only normal samples to train the model and trained model can be used for outlier detection. In this paper,…
ClassificationGeneral ClassificationGraph EmbeddingOne-Class Classification+3OCKELM+: 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)
Kernel method-based one-class classifier is mainly used for outlier or novelty detection. In this letter, kernel ridge regression (KRR) based one-class classifier (KOC) has been extended for learning using privileged inf…
General ClassificationNovelty DetectionOne-Class ClassificationOne-class classifierActive Authentication using an Autoencoder regularized CNN-based One-Class Classifier
Active authentication refers to the process in which users are unobtrusively monitored and authenticated continuously throughout their interactions with mobile devices. Generally, an active authentication problem is mode…
ClassificationGeneral ClassificationOne-Class ClassificationOne-class classifierUnsupervised Traffic Accident Detection in First-Person Videos
Recognizing abnormal events such as traffic violations and accidents in natural driving scenes is essential for successful autonomous driving and advanced driver assistance systems. However, most work on video anomaly de…
Anomaly DetectionAutonomous DrivingObject LocalizationOne-Class Classification+3Robust One-Class Kernel Spectral Regression
The kernel null-space technique and its regression-based formulation (called one-class kernel spectral regression, a.k.a. OC-KSR) is known to be an effective and computationally attractive one-class classification framew…
General ClassificationOne-Class ClassificationregressionDeep One-Class Classification Using Intra-Class Splitting
This paper introduces a generic method which enables to use conventional deep neural networks as end-to-end one-class classifiers. The method is based on splitting given data from one class into two subsets. In one-class…
ClassificationGeneral ClassificationOne-Class ClassificationOne-Class Convolutional Neural Network
We present a novel Convolutional Neural Network (CNN) based approach for one class classification. The idea is to use a zero centered Gaussian noise in the latent space as the pseudo-negative class and train the network …
Anomaly DetectionGeneral ClassificationNovelty DetectionOne-Class ClassificationGeneralizing Fingerprint Spoof Detector: Learning a One-Class Classifier
Prevailing fingerprint recognition systems are vulnerable to spoof attacks. To mitigate these attacks, automated spoof detectors are trained to distinguish a set of live or bona fide fingerprints from a set of known spoo…
One-Class ClassificationOne-class classifierActive Learning for One-Class Classification Using Two One-Class Classifiers
This paper introduces a novel, generic active learning method for one-class classification. Active learning methods play an important role to reduce the efforts of manual labeling in the field of machine learning. Althou…
Active LearningGeneral ClassificationOne-Class ClassificationVocal Bursts Valence PredictionOne-Class Feature Learning Using Intra-Class Splitting
This paper proposes a novel generic one-class feature learning method based on intra-class splitting. In one-class classification, feature learning is challenging, because only samples of one class are available during t…
ClassificationGeneral Classificationimage-classificationImage Classification+1OCLEP+: One-class Anomaly and Intrusion Detection Using Minimal Length of Emerging Patterns
This paper presents a method called One-class Classification using Length statistics of Emerging Patterns Plus (OCLEP+).
ClassificationGeneral ClassificationIntrusion DetectionOne-Class ClassificationFeature Learning for Fault Detection in High-Dimensional Condition-Monitoring Signals
Complex industrial systems are continuously monitored by a large number of heterogeneous sensors. The diversity of their operating conditions and the possible fault types make it impossible to collect enough data for lea…
Dimensionality ReductionFault DetectionOne-Class ClassificationOne-class classifier+1Deep One-Class Classification
Despite the great advances made by deep learning in many machine learning problems, there is a relative dearth of deep learning approaches for anomaly detection. Those approaches which do exist involve networks trai…
Anomaly DetectionClassificationDeep LearningOne-Class Classification+1CLEAR: Cumulative LEARning for One-Shot One-Class Image Recognition
This work addresses the novel problem of one-shot one-class classification. The goal is to estimate a classification decision boundary for a novel class based on a single image example. Our method exploits transfer learn…
ClassificationGeneral ClassificationOne-Class ClassificationTransfer LearningLocalized Multiple Kernel Learning for Anomaly Detection: One-class Classification
Multi-kernel learning has been well explored in the recent past and has exhibited promising outcomes for multi-class classification and regression tasks. In this paper, we present a multiple kernel learning approach for …
Anomaly DetectionClassificationGeneral ClassificationMulti-class Classification+2Multi-layer Kernel Ridge Regression for One-class Classification
In this paper, a multi-layer architecture (in a hierarchical fashion) by stacking various Kernel Ridge Regression (KRR) based Auto-Encoder for one-class classification is proposed and is referred as MKOC. MKOC has many l…
ClassificationGeneral ClassificationOne-Class ClassificationOne-class classifier+1