Deep residual LSTM with domain-invariance for remaining useful life prediction across domains
Currently developed unsupervised domain adaptation (UDA) methods have somewhat
improved the prognostic performance of cross-domain RUL prediction, but only optimizing …
improved the prognostic performance of cross-domain RUL prediction, but only optimizing …
Unsupervised structure-texture separation network for oracle character recognition
Oracle bone script is the earliest-known Chinese writing system of the Shang dynasty and is
precious to archeology and philology. However, real-world scanned oracle data are rare …
precious to archeology and philology. However, real-world scanned oracle data are rare …
Multi-branch convolutional neural networks with integrated cross-entropy for fault diagnosis in diesel engines
H Zhao, Z Mao, J Zhang, X Zhang… - Measurement Science …, 2021 - iopscience.iop.org
Fault diagnosis based on deep learning has become a hot research topic because of the
successful application of deep learning in other fields. Due to variable operating conditions …
successful application of deep learning in other fields. Due to variable operating conditions …
Extreme learning machine based on maximum weighted mean discrepancy for unsupervised domain adaptation
Y Si, J Pu, S Zang, L Sun - IEEE Access, 2020 - ieeexplore.ieee.org
Extreme Learning Machine (ELM) has shown fast learning speed and good generalization
property in single-domain problems, such as classification and regression. However, the …
property in single-domain problems, such as classification and regression. However, the …
The employment of domain adaptation strategy for improving the applicability of neural network-based coke quality prediction for smart cokemaking process
Y Qiu, Y Hui, P Zhao, M Wang, S Guo, B Dai, J Dou… - Fuel, 2024 - Elsevier
Precise coke quality prediction is essential for coke production process optimization to
achieve the reduction in energy consumption and CO 2 emissions, thus moving toward …
achieve the reduction in energy consumption and CO 2 emissions, thus moving toward …
Oracle character recognition using unsupervised discriminative consistency network
Ancient history relies on the study of ancient characters. However, real-world scanned
oracle characters are difficult to collect and annotate, posing a major obstacle for oracle …
oracle characters are difficult to collect and annotate, posing a major obstacle for oracle …
Continuous unsupervised domain adaptation using stabilized representations and experience replay
M Rostami - Neurocomputing, 2024 - Elsevier
We introduce an algorithm for tackling the problem of unsupervised domain adaptation
(UDA) in continual learning (CL) scenarios. The primary objective is to maintain model …
(UDA) in continual learning (CL) scenarios. The primary objective is to maintain model …
Learning discriminative feature via a generic auxiliary distribution for unsupervised domain adaptation
Traditional methods for unsupervised domain adaptation often leverage a projection matrix
or a neural network as the feature extractor or classifier, where the feature extractor shared …
or a neural network as the feature extractor or classifier, where the feature extractor shared …
Unsupervised Attention Regularization Based Domain Adaptation for Oracle Character Recognition
The study of oracle characters plays an important role in Chinese archaeology and
philology. However, the difficulty of collecting and annotating real-world scanned oracle …
philology. However, the difficulty of collecting and annotating real-world scanned oracle …
Transfer learning aid the prediction of sintering densification
W Zhouzhi, Z Xiaomin, Z Zhipeng, Z Hengjia… - Ceramics …, 2020 - Elsevier
In powder metallurgy engineering, the master sintering curve (MSC) is crucial for estimating
the mechanical properties of sintered products and optimizing sintering process parameters …
the mechanical properties of sintered products and optimizing sintering process parameters …