Results 51 to 60 of about 2,528 (182)

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

A randomized block Krylov method for tensor train approximation

Frontiers in Applied Mathematics and Statistics
Tensor train decomposition is a powerful tool to tackle high-dimensional large-scale tensor data and is not suffering from the curse of dimensionality. It relies on performing the singular value decomposition (SVD) of auxiliary unfolding matrices.
Gaohang Yu, Jinhong Feng, Zhongming Chen, Xiaohao Cai, Liqun Qi   +4 more
doaj   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Weighted t-Schatten-p Norm Minimization for Real Color Image Denoising

IEEE Access, 2020
In this paper, to fully exploit the spatial and spectral correlation information, we present a new real color image denoising scheme using tensor Schatten-p norm (t-Schatten-p norm) minimization based on t-SVD to recover the underlying low-rank tensor ...
Min Liu, Xinggan Zhang, Lan Tang
doaj   +1 more source

Hyper-Laplacian Regularized Multi-View Subspace Clustering With a New Weighted Tensor Nuclear Norm

IEEE Access, 2021
In this paper, we present a hyper-Laplacian regularized method WHLR-MSC with a new weighted tensor nuclear norm for multi-view subspace clustering. Specifically, we firstly stack the subspace representation matrices of the different views into a tensor ...
Qingjiang Xiao, Shiqiang Du, Jinmei Song, Yao Yu, Yixuan Huang   +4 more
doaj   +1 more source

Structural network efficiency predicts cognitive decline in cerebral small vessel disease

NeuroImage: Clinical, 2020
Cerebral small vessel disease (SVD) is a common disease in older adults and a major contributor to vascular cognitive impairment and dementia. White matter network damage is a potentially important mechanism by which SVD causes cognitive impairment ...
Esther M. Boot, Esther MC van Leijsen, Mayra I. Bergkamp, Roy P.C. Kessels, David G. Norris, Frank-Erik de Leeuw, Anil M. Tuladhar   +6 more
doaj   +1 more source

Quenching the Hubbard Model: Comparison of Nonequilibrium Green's Function Methods

Contributions to Plasma Physics, EarlyView.
ABSTRACT We benchmark nonequilibrium Green's function (NEGF) approaches for interaction quenches in the half‐filled Fermi–Hubbard model in one and two dimensions. We compare fully self‐consistent two‐time Kadanoff–Baym equations (KBE), the generalized Kadanoff–Baym ansatz (GKBA), and the recently developed NEGF‐based quantum fluctuations approach (NEGF‐
Jan‐Philip Joost, Christopher Makait, Alexander Osterkorn, Erik Schroedter   +3 more
wiley   +1 more source

HOSVD++: A Tensor-Based High Order SVD++ Recommendation System

Big Data Mining and Analytics
In the context of big data enabling e-commerce, content platforms, and social networks, Recommendation Systems (RSs) play a crucial role in providing personalized items and services suggestions to users.
Jiawei Wang, Sai Gu, Xiaotong Zhou, Ren Li, Yuxiang Zheng, Debin Liu, Ruonan Zhao, Huazhong Liu, M. Jamal Deen   +8 more
doaj   +1 more source

Four Directions, One Solution: Enabling Rapid Diffusion Tensor MRI for Ultra‐Low Field Using Deep Learning

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose This study revisits the tetrahedral encoding strategy originally proposed to accelerate Diffusion Tensor Magnetic Resonance Imaging (DT‐MRI) by reducing the requisite number of diffusion‐weighted measurements to four. We examine its practical limitations and explore how artificial intelligence (AI) can extend its utility. Specifically,
Joshua Mawuli Ametepe, James Gholam, Leandro Beltrachini, Mara Cercignani, Derek Kenton Jones   +4 more
wiley   +1 more source

Real Color Image Denoising Using t-Product- Based Weighted Tensor Nuclear Norm Minimization

IEEE Access, 2019
Color images can be seen as third-order tensors with column, row and color modes. Considering two inherent characteristics of a color image including the non-local self-similarity (NSS) and the cross-channel correlation, we extract non-local similar ...
Min Liu, Xinggan Zhang, Lan Tang
doaj   +1 more source