Area of research
Cognitive Neuroscience · Neurology
Research interest
Research focused on Artificial intelligence and Segmentation, with related work in Discriminative model, Convolutional neural network, Diffusion MRI. Notable publications include 'Spatial–Temporal Complex Graph Convolution Network for Traffic Flow Prediction', 'FTransCNN: Fusing Transformer and a CNN based on fuzzy logic for uncertain medical image segmentation', and 'Attention-Diffusion-Bilinear Neural Network for Brain Network Analysis'.
Multimodal multi-instance evidence fusion neural networks for cancer survival prediction
Global-local graph convolutional broad network for hyperspectral image classification
Multigranularity Fuzzy Autoencoder for Discriminative Feature Selection in High-Dimensional Data
F2CAU-Net: A dual fuzzy medical image segmentation cascade method based on fuzzy feature learning
Local structural–functional coupling with counterfactual explanations for epilepsy prediction
Document-Level Neural Machine Translation With Document Embeddings
The fuzzy hypergraph neural network model based on sparse k-nearest neighborhood granule
Class-specific semi-supervised feature selection with fuzzy convex balling information granularity
MGC-DMF: A traffic flow forecasting method based on multi-graph spatio-temporal convolution and dynamic metric fusion with multi-source basic information
FEU-Diff: A Diffusion Model With Fuzzy Evidence-Driven Dynamic Uncertainty Fusion for Medical Image Segmentation
Counterfactual explanations of tree based ensemble models for brain disease analysis with structure function coupling
FCAformer: Fuzzy-Enhanced Class-Aware Attention Based Transformer for Weakly Supervised Histopathology Image Segmentation
Multi-view fusion neural networks for heterogeneous graph representation learning
FMDNN: A Fuzzy-Guided Multigranular Deep Neural Network for Histopathological Image Classification
FDiff-Fusion: Denoising diffusion fusion network based on fuzzy learning for 3D medical image segmentation
Hyperspectral image classification using feature fusion fuzzy graph broad network
AGBN-Transformer: Anatomy-guided brain network transformer for schizophrenia diagnosis
An infrared and visible image fusion using knowledge measures for intuitionistic fuzzy sets and Swin Transformer
Cascaded Two-Stage Feature Clustering and Selection via Separability and Consistency in Fuzzy Decision Systems
Dynamic evidence fusion neural networks with uncertainty theory and its application in brain network analysis
Evolutionary multistage multitasking method for feature selection in imbalanced data
BiFuG2-Spark: Bi-Directional Fuzzy Granular-Cabin Parallel Attribute Reduction Accelerator With Granular-Group Collaboration
Dual-Channel Fuzzy Interaction Information Fused Feature Selection With Fuzzy Sparse and Shared Granularities
C2F-Explainer: Explaining Transformers Better Through a Coarse-to-Fine Strategy
A distributed attribute reduction based on neighborhood evidential conflict with Apache Spark
MFCA: Collaborative prediction algorithm of brain age based on multimodal fuzzy feature fusion
Pheromone-guided parallel rough hypercuboid attribute reduction algorithm
MMF-NNs: Multi-modal Multi-granularity Fusion Neural Networks for brain networks and its application to epilepsy identification
Multi-association evidential feature selection and its application to identifying schizophrenia
Quality-aware fuzzy min–max neural networks for dynamic brain network analysis and its application to schizophrenia identification