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Non-local tensor sparse representation and tensor low rank regularization for dynamic MRI reconstruction
Dynamic Magnetic Resonance Imaging (DMRI) reconstruction is a challenging theme in image processing. A variety of dimensionality reduction methods...
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Sparse multi-label feature selection via dynamic graph manifold regularization
Multi-label feature selection is a hot topic in multi-label high-dimensional data processing. However, some multi-label feature selection models use...
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Damage identification based on topology optimization and Lasso regularization
In this paper, we present a damage identification method for small damages based on topology optimization and Lasso regularization. In particular,...
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Identifying spatiotemporal information of the point pollutant source indoors based on the adjoint-regularization method
Fast and accurate identification of the pollutant source location and release rate is important for improving indoor air quality. From the...
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Frictional node-to-segment contact analysis based on the modified area regularization technique
Node-to-segment (NTS) contact algorithm based on the penalty method remains significant in the industry owing to its computational efficiency and...
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A Time Regularization Scheme for Spacecraft Trajectories Subject to Multi-Body Gravity
A time regularization scheme is introduced that facilitates trajectory optimization in multi-body regimes. The time transformation function allows...
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Enhancing framelet GCNs with generalized p-Laplacian regularization
Graph neural networks (GNNs) have achieved remarkable results for various graph learning tasks. However, one of the recent challenges for GNNs is to...
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Regularization based reweighted estimation algorithms for nonlinear systems in presence of outliers
Outliers usually occur during industrial data collection process and can lead to poor system identification performance. This paper considers the...
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Three-stage training and orthogonality regularization for spoken language recognition
Spoken language recognition has made significant progress in recent years, for which automatic speech recognition has been used as a parallel branch...
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Vectorized Trigonometric Regularization for Singular Control Problems with Multiple State Path Constraints
Optimal control problems (OCPs) with a control-affine Hamiltonian may lead to extremal solutions with singular control arcs. The presence of singular...
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Consistency regularization for deep semi-supervised clustering with pairwise constraints
Due to its powerful learning capabilities for high-dimensional and complex data, deep semi-supervised clustering algorithms often outperform...
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Unsupervised learning of optical flow in a multi-frame dynamic environment using temporal dynamic modeling
For visual estimation of optical flow, which is crucial for various vision analyses, unsupervised learning by view synthesis has emerged as a...
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A nonlinear model for dynamic performance analysis of gas foil bearing-rotor system considering frictional contacts
The dynamic behaviors of gas foil bearing-rotor system are greatly affected by the dam** resulting from friction inside foil structure. However,...
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Random vector functional link network with L21 norm regularization for robot visual servo control with feature constraint
Uncalibrated visual servoing control still encounters some challenges, such as calculating the interaction matrix with less cost and kee** the...
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Joint image pansharpening and registration via structure tensor total variation regularization
Pansharpening has been extensively studied in recent years. However, one drawback of the known image fusion methods is that the fusion performance is...
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ORAD: a new framework of offline Reinforcement Learning with Q-value regularization
Offline Reinforcement Learning (RL) defines a framework for learning from previously collected static buffer. However, offline RL is prone to...
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Prediction of dynamic systems driven by Lévy noise based on deep learning
Predicting strongly noise-driven dynamic systems has always been a difficult problem due to their chaotic properties. In this study, we investigated...
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RTR-DPD: reweighted tikohonov regularization for blind deblurring via dual principles of discriminativeness
Blind deblurring has undergone rapid development since the variational Bayes method of Fergus et al. about 15 years ago. Nowadays, it is generally...
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A Regularization Factor-Based Approach to Anomaly Detection Using Contrastive Learning
Anomaly detection methods are introduced to remove abnormalities from specific datasets. In the paper, mean shifted contrastive loss for anomaly...
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A dynamic few-shot learning framework for medical image stream mining based on self-training
Few-shot semantic segmentation (FSS) has been widely used in the field of information medicine and intelligent diagnosis. Due to the high cost of...
