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Unsupervised Domain Adversarial Network for Few-Sample Fault Detection in Industrial Processes

https://doi.org/10.2139/ssrn.4659527
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Domain-Adversarial Training of Neural Networks
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Domain-specific sentiment analysis for tweets during hurricanes (DSSA-H): A domain-adversarial neural-network-based approach
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Deep balanced domain adaptation neural networks for fault diagnosis of planetary gearboxes with limited labeled data
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Equalization Loss for Long-Tailed Object Recognition
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C2AM Loss: Chasing a Better Decision Boundary for Long-Tail Object Detection
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Deep Domain-Adversarial Anomaly Detection With One-Class Transfer Learning
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A Comprehensive Survey on Transfer Learning
inferredcites →https://doi.org/10.1109/jsen.2020.2975286openalex-extracted
A Deep Adversarial Transfer Learning Network for Machinery Emerging Fault Detection
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Additive Margin Softmax for Face Verification
inferredcites →https://doi.org/10.1109/tase.2019.2956087openalex-extracted
Deep Discriminative Representation Learning for Nonlinear Process Fault Detection
inferredcites →https://doi.org/10.1109/tcyb.2021.3050398openalex-extracted
MoniNet With Concurrent Analytics of Temporal and Spatial Information for Fault Detection in Industrial Processes
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Modeling and Monitoring Between-Mode Transition of Multimodes Processes
inferredcites →https://doi.org/10.1109/tii.2018.2810822openalex-extracted
Canonical Variate Dissimilarity Analysis for Process Incipient Fault Detection
inferredcites →https://doi.org/10.1109/tii.2018.2886048openalex-extracted
Learning Deep Correlated Representations for Nonlinear Process Monitoring
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Safety Poka Yoke in Zero-Defect Manufacturing Based on Digital Twins
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Convolutional Long Short-Term Memory Autoencoder-Based Feature Learning for Fault Detection in Industrial Processes
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A Survey on Transfer Learning
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A Two-Stage Transfer Adversarial Network for Intelligent Fault Diagnosis of Rotating Machinery With Multiple New Faults
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Dynamically Weighted Balanced Loss: Class Imbalanced Learning and Confidence Calibration of Deep Neural Networks
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Deep Neural Network-Embedded Stochastic Nonlinear State-Space Models and Their Applications to Process Monitoring
inferredcites →https://doi.org/10.1109/tpami.2018.2858826openalex-extracted
Focal Loss for Dense Object Detection
inferredcites →https://doi.org/10.1109/tpami.2019.2914680openalex-extracted
Deep Imbalanced Learning for Face Recognition and Attribute Prediction
inferredcites →https://doi.org/10.1145/3360309openalex-extracted
Transfer Learning with Dynamic Distribution Adaptation
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A Review of Deep Transfer Learning and Recent Advancements
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Learning Transferable Features with Deep Adaptation Networks
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Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
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