We propose a novel method, LoLep, which regresses Locally-Learned planes...
It can be difficult to identify trends and perform quality control in la...
Existing refinement methods gradually lose their ability to further impr...
We present a novel self-supervised algorithm named MotionHint for monocu...
In stable coronary artery disease (CAD), reduction in mortality and/or
m...
Objective: Multi-modal functional magnetic resonance imaging (fMRI) can ...
Collaborative simultaneous localization and mapping (SLAM) approaches pr...
Functional connectivity (FC) has been widely used to study brain network...
Resting-state functional magnetic resonance imaging (rs-fMRI)-derived
fu...
Functional connectivity (FC) has become a primary means of understanding...
Multimodal fusion benefits disease diagnosis by providing a more
compreh...
In recent years, a comprehensive study of multi-view datasets (e.g.,
mul...
The robust Chinese remainder theorem (CRT) has been recently proposed fo...
Human brain development is a complex and dynamic process that is affecte...
Modern robotic systems have become an alternative to humans to perform r...
The study of healthy brain development helps to better understand the br...
Inter-process communication (IPC) is one of the core functions of modern...
In this study, we tested the interaction effect of multimodal datasets u...
Reducing the number of false positive discoveries is presently one of th...
Many unsupervised kernel methods rely on the estimation of the kernel
co...
Kernel and Multiple Kernel Canonical Correlation Analysis (CCA) are empl...
In genome-wide interaction studies, to detect gene-gene interactions, mo...
Imaging genetic research has essentially focused on discovering unique a...
To the best of our knowledge, there are no general well-founded robust
m...