Results 51 to 60 of about 3,427 (187)

Sylvester Tikhonov-regularization methods in image restoration

Journal of Computational and Applied Mathematics, 2007
The authors consider large-scale linear discrete ill posed problems where the right-hand side contains noise. In order to control the effect of the noise on the solution, regularization techniques such as Tikhonov are needed. In many applications the coefficient matrix is given as a Kronecker product of two matrices and then the Tikhonov regularization
Bouhamidi, A., Jbilou, K.
openaire   +1 more source

Regularized Joint Reconstruction and Slab Combination for Accelerated Three‐Dimensional Multi‐Slab Diffusion‐Weighted Imaging Using Multi‐Scale Energy Models

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To jointly reconstruct high‐resolution diffusion‐weighted volumes and eliminate slab‐boundary artifacts while preserving fine anatomical detail from undersampled 3D multi‐slab k‐space acquisitions. Methods A bilinear forward model was formulated to describe the 3D multi‐slab acquisition, treating the image volume and slab excitation ...
Reza Ghorbani, Jyothi Rikhab Chand, Chu‐Yu Lee, Mathews Jacob, Merry Mani   +4 more
wiley   +1 more source

Prop-cut: A mesh cutting method based on Tikhonov regularization [PDF]

2009 11th IEEE International Conference on Computer-Aided Design and Computer Graphics, 2009
We present an interactive mesh cutting method in this paper, which is based on a formulation of semi-supervised learning. Users first assign foreground and background seed faces on a given triangular mesh by sketch lines. Then the system computes a scalar field across the mesh.
Hongxin Zhang 0001, Juan Wang
openaire   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +4 more
wiley   +1 more source

In situ mapping of iron oxidation in laminar metal fuel flames using X‐ray absorption spectroscopy

Journal of Synchrotron Radiation, EarlyView.
For the first time an iron metal flame has been mapped by in situ X‐ray absorption spectroscopy. Strong gradients in oxidation state and phase composition across the metallic core and the flame front were found with FeO peaking at the visible flame front and Fe3O4 forming further beyond.Metal fuels such as iron are promising carbon‐free energy carriers
Lukas Braun, Fabian P. Hagen, Michal Fedoryk, Malte Seitz, Björn Stelzner, Dimosthenis Trimis, Jan-Dierk Grunwaldt, Dmitry E. Doronkin   +7 more
wiley   +1 more source

Not all Temperature Shocks are Alike: Disentangling Heat and High Temperature Shocks and Their Effects on Inflation in Australia

Economic Record, EarlyView.
We study the effects of heat and high temperature shocks on inflation in Australia using monthly, state‐level temperature anomaly data via two stages. In the first stage, we decompose temperature anomalies into orthogonal components using a structural vector autoregression with long‐run restrictions.
Tan Dat Huynh, Mengheng Li
wiley   +1 more source

Research on Dynamic Load Identification Based on Explicit Wilson-θ and Improved Regularization Algorithm

Shock and Vibration, 2019
In the research of dynamic load identification, the method of obtaining kernel function matrix is usually rather cumbersome. To solve this problem, an explicit dynamic load identification algorithm based on the Wilson-θ (DLIAEW) method is proposed to ...
Yuchuan Fan, Chunyu Zhao, Hongye Yu
doaj   +1 more source

A Horse Race of Machine‐Learning Methods to Predict Banking Crises

International Finance, EarlyView.
ABSTRACT To examine if one machine‐learning model can consistently elucidate financial vulnerabilities, both over time and across levels of development, this paper applies 13 machine‐learning algorithms to evaluate comparative forecasting performance across several banking crises.
Emile du Plessis
wiley   +1 more source

Inter‐Shot Motion Correction of Segmented 3D‐GRASE ASL Perfusion Imaging With Self‐Navigation and CAIPI

Magnetic Resonance in Medicine, Volume 96, Issue 4, Page 1557-1571, October 2026.
ABSTRACT Purpose Segmented 3D Gradient and Spin Echo (GRASE) is commonly used in Arterial Spin Labeling (ASL) perfusion imaging. However, it is vulnerable to inter‐shot motion, leading to subtraction errors that cannot be corrected. We developed a retrospective self‐navigated inter‐shot motion correction method for segmented 3D‐GRASE ASL imaging with ...
Minhao Hu, Frederik J. Lange, Peter Jezzard, Joseph G. Woods, Mark Chiew, Thomas W. Okell   +5 more
wiley   +1 more source

Laterally Oscillating Trajectory for Undersampling Slices: LOTUS

Magnetic Resonance in Medicine, Volume 96, Issue 4, Page 1682-1695, October 2026.
ABSTRACT Purpose While spiral sampling offers SNR advantages for diffusion MRI, its acceleration with simultaneous multislice remains relatively unexplored. This study introduces Laterally Oscillating Trajectory for Undersampling Slices (LOTUS), which is a 3D spiral‐like k‐space trajectory that aims to minimize g‐factor via controlled incoherent ...
Mayuri Sothynathan, Paul I. Dubovan, Corey A. Baron   +2 more
wiley   +1 more source