A5101760158- Functional Brain Connectivity Studies
- Advanced Neuroimaging Techniques and Applications
- Traffic control and management
- Neural dynamics and brain function
- Mental Health Research Topics
- Remote Sensing and Land Use
- Advanced Computational Techniques and Applications
- Geographic Information Systems Studies
- Data Management and Algorithms
- Constraint Satisfaction and Optimization
- Discourse Analysis in Language Studies
- Advanced MRI Techniques and Applications
- Alzheimer's disease research and treatments
- Neuroscience and Music Perception
- Second Language Acquisition and Learning
- Advanced Algorithms and Applications
- EEG and Brain-Computer Interfaces
- Advanced Image Fusion Techniques
- Image and Video Quality Assessment
- Neural Networks Stability and Synchronization
- Transportation Planning and Optimization
- Vehicle Dynamics and Control Systems
- Soil Geostatistics and Mapping
- Visual Attention and Saliency Detection
- Cellular Automata and Applications
Xi’an University of Posts and Telecommunications
2025
Lanzhou University
2020-2021
Zhejiang University
2021
Chinese Academy of Surveying and Mapping
2020
Zhengzhou University
2012
ABSTRACT Facial expression recognition (FER) is significant in many application scenarios, such as driving scenarios with very different lighting conditions between day and night. Existing methods primarily focus on eliminating the negative effects of pose identity information FER, but overlook challenges posed by variations. So, this work proposes an efficient illumination‐invariant dynamic FER method. To augment robustness to illumination variance, contrast normalisation introduced form a...
It is important to improve identification accuracy for possible early intervention of major depressive disorder (MDD). Recently, effective connectivity (EC), defined as the directed influence spatially distant brain regions on each other, has been used find dysfunctional organization networks in MDD. However, little known about ability whole-brain resting-state EC features Here, we employed by analysis perform MDD diagnosis.In this study, proposed a high-order network capturing high-level...
Major depressive disorder (MDD) is accompanied by abnormal changes in functional connectivities (FC) among brain regions. However, most studies estimated the pairwise connectivity without thorough consideration of influence other regions and assumed that was static, which may be insufficient for accurate identification pathological mechanisms underlying MDD. The purpose this study to explore MDD based on dynamic FC taking into account. We performed time-varying analysis resting-state...
Jointly analyzing structural and functional brain networks enables a better understanding of pathological underpinnings irritable bowel syndrome (IBS). Multiplex network analysis provides novel framework to study complex consisting different types connectivity patterns in multimodal data.In the present work, we integrated multiplex network. Then, metrics inner-layer/inter-layer hub nodes were investigated through 34 patients with IBS 33 healthy controls.Significantly differential degree both...
Effective estimation of brain network connectivity enables better unraveling the extraordinary complexity interactions regions and helps in auxiliary diagnosis psychiatric disorders. Considering different modalities can provide comprehensive characterizations connectivity, we propose message-passing-based nonlinear fusion (MP-NNF) algorithm to estimate multimodal connectivity. In proposed method, initial functional structural networks were computed from fMRI DTI separately. Then, update...
Learning a deep structure representation for complex information networks is vital research area, and assessing the quality of stereoscopic images or videos challenging due to 3D factors. In this paper, we explore how extract effective features enhance prediction accuracy perceptual assessment. Inspired by human visual system machine learning technique, propose no‐reference assessment scheme images. More specifically, statistical gradient magnitude Laplacian Gaussian responses are extracted...
In the geographic information system field, identifying and cleaning self-intersected polygons to achieve simple is a basic core issue. traditional research, were identified by topological relationship between line segments that form polygons. However, in process of map generalization or spatial overlay calculations, elimination self-intersection not sufficient. Elements (vertices segments) are topologically separated but whose distance smaller than minimum visible on also need be considered...
In the field of cartography and geographic information systems, eliminating self-intersection problems is a key step in improving reliability robustness spatial data representations, especially for multipart polygon with one outer ring (MPOOR). traditional studies, self-intersected MPOORs were identified by topological intersection relationships between line segments, but during map generalization or calculations, identifying only self-intersections insufficient. Elements (vertices segments)...