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Deep Domain-Adversarial Anomaly Detection With One-Class Transfer Learning

https://doi.org/10.1109/jas.2023.123228
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Outgoing claims: the papers this work cites, builds on, or argues with.

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A Survey on Deep Transfer Learning
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Domain Adaptation for Automatic OLED Panel Defect Detection Using Adaptive Support Vector Data Description
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Pattern recognition-based chillers fault detection method using Support Vector Data Description (SVDD)
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Transfer learning-based one-class dictionary learning for recommendation data stream
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Online detection of bearing incipient fault with semi-supervised architecture and deep feature representation
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Early fault diagnosis of rolling bearings based on hierarchical symbol dynamic entropy and binary tree support vector machine
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Detection and identification of windmill bearing faults using a one-class support vector machine (SVM)
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Online detection for bearing incipient fault based on deep transfer learning
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Fault anomaly detection of synchronous machine winding based on isolation forest and impulse frequency response analysis
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VAE-based Deep SVDD for anomaly detection
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Transfer learning with one-class data
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Transfer learning for one class SVM adaptation to limited data distribution change
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Intrusion Detection System (IDS): Anomaly Detection Using Outlier Detection Approach
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inferredcites →https://doi.org/10.1109/access.2020.3022646openalex-snapshot
Latent Feature Decentralization Loss for One-Class Anomaly Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.572openalex-snapshot
Deep Hashing Network for Unsupervised Domain Adaptation
inferredcites →https://doi.org/10.1109/cvpr.2018.00566openalex-snapshot
Domain Generalization with Adversarial Feature Learning
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00424openalex-snapshot
Uninformed Students: Student-Teacher Anomaly Detection With Discriminative Latent Embeddings
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01219openalex-snapshot
Self-Trained Deep Ordinal Regression for End-to-End Video Anomaly Detection
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00283openalex-snapshot
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
inferredcites →https://doi.org/10.1109/cvprw59228.2023.00297openalex-snapshot
Anomaly Detection with Domain Adaptation
inferredcites →https://doi.org/10.1109/icdm51629.2021.00098openalex-snapshot
FRAUDRE: Fraud Detection Dual-Resistant to Graph Inconsistency and Imbalance
inferredcites →https://doi.org/10.1109/ijcnn.2018.8489068openalex-snapshot
Clustering and Unsupervised Anomaly Detection with l2 Normalized Deep Auto-Encoder Representations
inferredcites →https://doi.org/10.1109/tie.2016.2627020openalex-snapshot
Deep Model Based Domain Adaptation for Fault Diagnosis
inferredcites →https://doi.org/10.1109/tie.2017.2650873openalex-snapshot
Application of Bandwidth EMD and Adaptive Multiscale Morphology Analysis for Incipient Fault Diagnosis of Rolling Bearings
inferredcites →https://doi.org/10.1109/tim.2018.2800978openalex-snapshot
Early Fault Detection Approach With Deep Architectures
inferredcites →https://doi.org/10.1109/tim.2019.2903699openalex-snapshot
A New Online Detection Approach for Rolling Bearing Incipient Fault via Self-Adaptive Deep Feature Matching
inferredcites →https://doi.org/10.1109/tim.2020.3038596openalex-snapshot
A New Structured Domain Adversarial Neural Network for Transfer Fault Diagnosis of Rolling Bearings Under Different Working Conditions
inferredcites →https://doi.org/10.1109/tim.2022.3159010openalex-snapshot
An Interpretable Deep Transfer Learning-Based Remaining Useful Life Prediction Approach for Bearings With Selective Degradation Knowledge Fusion
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Partial Transfer Learning of Multidiscriminator Deep Weighted Adversarial Network in Cross-Machine Fault Diagnosis
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Pebl:web page classification without negative examples
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A Comprehensive Survey on Graph Anomaly Detection With Deep Learning
inferredcites →https://doi.org/10.1109/tnn.2010.2091281openalex-snapshot
Domain Adaptation via Transfer Component Analysis
inferredcites →https://doi.org/10.1109/tr.2018.2882682openalex-snapshot
A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings
inferredcites →https://doi.org/10.1137/1.9781611974973.11openalex-snapshot
Outlier Detection with Autoencoder Ensembles
inferredcites →https://doi.org/10.1145/3439950openalex-snapshot
Deep Learning for Anomaly Detection
inferredcites →https://doi.org/10.1145/3459637.3482209openalex-snapshot
Unsupervised Cross-system Log Anomaly Detection via Domain Adaptation
inferredcites →https://doi.org/10.1145/3474379openalex-snapshot
eFraudCom: An E-commerce Fraud Detection System via Competitive Graph Neural Networks
inferredcites →https://doi.org/10.1145/3488560.3498389openalex-snapshot
ComGA
inferredcites →https://doi.org/10.1609/aaai.v33i01.33011286openalex-snapshot
One-Class Adversarial Nets for Fraud Detection
inferredcites →https://doi.org/10.48550/arxiv.1412.3474openalex-snapshot
Deep Domain Confusion: Maximizing for Domain Invariance
inferredcites →https://doi.org/10.48550/arxiv.2104.09793openalex-snapshot
What is Wrong with One-Class Anomaly Detection?

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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