Area of research
Cognitive Neuroscience · Artificial Intelligence
Research interest
Research interests include Computer science, Artificial intelligence, Fuzzy logic, Artificial neural network, Feature selection, and Pattern recognition (psychology).
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
A survey on feature selection techniques for biomedical data: Methods and applications
FCAformer: Fuzzy-Enhanced Class-Aware Attention Based Transformer for Weakly Supervised Histopathology Image Segmentation
ECG Adaptive Synthesis With Multigranular Fuzzy EASNN: Enhancing Wearable Cardiac Monitoring
FAMU-Net: A network method for segmentation of retinal blood vessels based on fuzzy axial attention and multi-scale feature fusion
FMDNN: A Fuzzy-Guided Multigranular Deep Neural Network for Histopathological Image Classification
Quality-aware fuzzy min–max neural networks for dynamic brain network analysis and its application to schizophrenia identification
Token Dropping for Efficient BERT Pretraining