相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Modified Deep Autoencoder Driven by Multisource Parameters for Fault Transfer Prognosis of Aeroengine
Zhiyi He et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2022)
Automatic detection of COVID-19 from chest CT scan and chest X-Rays images using deep learning, transfer learning and stacking
Ebenezer Jangam et al.
APPLIED INTELLIGENCE (2022)
Symplectic weighted sparse support matrix machine for gear fault diagnosis
Xin Li et al.
MEASUREMENT (2021)
Determination of COVID-19 pneumonia based on generalized convolutional neural network model from chest X-ray images
Adi Alhudhaif et al.
EXPERT SYSTEMS WITH APPLICATIONS (2021)
Short-term predictions of multiple wind turbine power outputs based on deep neural networks with transfer learning
Xin Liu et al.
ENERGY (2021)
Anomaly Detection of Industrial Control Systems Based on Transfer Learning
Weiping Wang et al.
TSINGHUA SCIENCE AND TECHNOLOGY (2021)
Deep Learning-Based Partial Domain Adaptation Method on Intelligent Machinery Fault Diagnostics
Xiang Li et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2021)
A transfer convolutional neural network for fault diagnosis based on ResNet-50
Long Wen et al.
NEURAL COMPUTING & APPLICATIONS (2020)
Deep Residual Shrinkage Networks for Fault Diagnosis
Minghang Zhao et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)
Deep Learning Algorithms for Bearing Fault Diagnosticsx&x2014;A Comprehensive Review
Shen Zhang et al.
IEEE ACCESS (2020)
Learning transferable features in deep convolutional neural networks for diagnosing unseen machine conditions
Te Han et al.
ISA TRANSACTIONS (2019)
Generalization of deep neural network for bearing fault diagnosis under different working conditions using multiple kernel method
Zenghui An et al.
NEUROCOMPUTING (2019)
Cross-Domain Fault Diagnosis Using Knowledge Transfer Strategy: A Review
Huailiang Zheng et al.
IEEE ACCESS (2019)
A novel gearbox fault feature extraction and classification using Hilbert empirical wavelet transform, singular value decomposition, and SOM neural network
Boualem Merainani et al.
JOURNAL OF VIBRATION AND CONTROL (2018)
Bearing vibration data collected under time-varying rotational speed conditions
Huan Huang et al.
DATA IN BRIEF (2018)
Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification
Chen Lu et al.
SIGNAL PROCESSING (2017)
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
Hoo-Chang Shin et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)
A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings
Akhand Rai et al.
TRIBOLOGY INTERNATIONAL (2016)
A Survey of Fault Diagnosis and Fault-Tolerant Techniques-Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches
Zhiwei Gao et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2015)
Prognostics and health management design for rotary machinery systems-Reviews, methodology and applications
Jay Lee et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2014)
From Model, Signal to Knowledge: A Data-Driven Perspective of Fault Detection and Diagnosis
Xuewu Dai et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2013)
Domain Adaptation via Transfer Component Analysis
Sinno Jialin Pan et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2011)
A Survey on Transfer Learning
Sinno Jialin Pan et al.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2010)
Integrating structured biological data by Kernel Maximum Mean Discrepancy
Karsten M. Borgwardt et al.
BIOINFORMATICS (2006)
分享论文
