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Two‐step support vector data description for dynamic, non‐linear, and non‐Gaussian processes monitoring

Canadian journal of chemical engineering, 2020-10, Vol.98 (10), p.2109-2124

2020

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Semi-supervised subclass support vector data description for image and video classification

Neurocomputing (Amsterdam), 2018-02, Vol.278, p.51-61

2018

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Unsupervised feature learning with C-SVDDNet

Pattern recognition, 2016-12, Vol.60, p.473-485

2016

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Large-margin multiple kernel ℓp-SVDD using Frank–Wolfe algorithm for novelty detection

Pattern recognition, 2024-04, Vol.148, Article 110189

Rahimzadeh Arashloo, Shervin

2024

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Density weighted support vector data description

Expert systems with applications, 2014-06, Vol.41 (7), p.3343-3350

2014

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Health evaluation of axial piston pumps based on density weighted support vector data description

Reliability engineering & system safety, 2023-09, Vol.237, p.109354, Article 109354

2023

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Combining motion and appearance cues for anomaly detection

Pattern recognition, 2016-03, Vol.51, p.443-452

2016

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Pattern recognition-based chillers fault detection method using Support Vector Data Description (SVDD)

Applied energy, 2013-12, Vol.112, p.1041-1048

2013

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Unsupervised Anomaly Detection With LSTM Neural Networks

IEEE transaction on neural networks and learning systems, 2020-08, Vol.31 (8), p.3127-3141

2020

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An Online Fault Detection and Remaining Life Prediction Method Based on SVDD for Rolling Bearings

IEEE transactions on instrumentation and measurement, 2024-01, Vol.73, p.1-1

2024

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Research on online anomaly detection methods for bearing degradation

Measurement science & technology, 2024-08, Vol.35 (8), p.85003

2024

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Unsupervised Homography Estimation with Pixel-level SVDD

IEEE transactions on circuits and systems for video technology, 2024, p.1-1

2024

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The manifold regularized SVDD for noisy label detection

Information sciences, 2023-01, Vol.619, p.235-248

2023

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Detecting wind turbine anomalies using nonlinear dynamic parameters-assisted machine learning with normal samples

Reliability engineering & system safety, 2023-05, Vol.233, p.109092, Article 109092

2023

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Vibration anomaly detection of wind turbine based on temporal convolutional network and support vector data description

Engineering structures, 2024-05, Vol.306, p.117848, Article 117848

2024

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ADS-B anomaly data detection model based on VAE-SVDD

Computers & security, 2021-05, Vol.104, p.102213, Article 102213

2021

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A New Online Detection Approach for Rolling Bearing Incipient Fault via Self-Adaptive Deep Feature Matching

IEEE transactions on instrumentation and measurement, 2020-02, Vol.69 (2), p.443-456

2020

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Automobile Driver Fingerprinting: A New Machine Learning Based Authentication Scheme

IEEE transactions on industrial informatics, 2020-02, Vol.16 (2), p.1417-1426

2020

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Abnormal identification of oil monitoring based on LSTM and SVDD

Wear, 2023-08, Vol.526-527, p.204793, Article 204793

2023

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Active anomaly detection based on deep one-class classification

Pattern recognition letters, 2023-03, Vol.167, p.18-24

2023

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Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description

Journal of engineering for gas turbines and power, 2023-09, Vol.145 (9)

2023

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A data-driven algorithm to detect false data injections targeting both frequency regulation and market operation in power systems

International journal of electrical power & energy systems, 2022-12, Vol.143, p.108409, Article 108409

2022

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A novel quality inspection method of compressors based on Deep SVDD and CWGAN-XGBoost

International journal of refrigeration, 2024-01, Vol.157, p.159-171

2024

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Pipeline Leak Detection by Using Time-Domain Statistical Features

IEEE sensors journal, 2017-10, Vol.17 (19), p.6431-6442

2017

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Hyperspectral image target detection via integrated background suppression with adaptive weight selection

Neurocomputing (Amsterdam), 2018-11, Vol.315, p.59-67

2018

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Two‐step support vector data description for dynamic, non‐linear, and non‐Gaussian processes monitoring

Semi-supervised subclass support vector data description for image and video classification

Unsupervised feature learning with C-SVDDNet

Large-margin multiple kernel ℓp-SVDD using Frank–Wolfe algorithm for novelty detection

Density weighted support vector data description

Health evaluation of axial piston pumps based on density weighted support vector data description

Combining motion and appearance cues for anomaly detection

Pattern recognition-based chillers fault detection method using Support Vector Data Description (SVDD)

Unsupervised Anomaly Detection With LSTM Neural Networks

An Online Fault Detection and Remaining Life Prediction Method Based on SVDD for Rolling Bearings

Research on online anomaly detection methods for bearing degradation

Unsupervised Homography Estimation with Pixel-level SVDD

The manifold regularized SVDD for noisy label detection

Detecting wind turbine anomalies using nonlinear dynamic parameters-assisted machine learning with normal samples

Vibration anomaly detection of wind turbine based on temporal convolutional network and support vector data description

ADS-B anomaly data detection model based on VAE-SVDD

A New Online Detection Approach for Rolling Bearing Incipient Fault via Self-Adaptive Deep Feature Matching

Automobile Driver Fingerprinting: A New Machine Learning Based Authentication Scheme

Abnormal identification of oil monitoring based on LSTM and SVDD

Active anomaly detection based on deep one-class classification

Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description

A data-driven algorithm to detect false data injections targeting both frequency regulation and market operation in power systems

A novel quality inspection method of compressors based on Deep SVDD and CWGAN-XGBoost

Pipeline Leak Detection by Using Time-Domain Statistical Features

Hyperspectral image target detection via integrated background suppression with adaptive weight selection

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