Area of research
Artificial Intelligence · Computer Vision and Pattern Recognition
Research interest
Research interests include Face and Expression Recognition, Stochastic Gradient Optimization Techniques, Sparse and Compressive Sensing Techniques, and Domain Adaptation and Few-Shot Learning.
Study on the cathode 3D flow field with main/sub channel and transition area structure for proton exchange membrane fuel cell
Trustworthy Clinical Thinking in MLLMs: Hierarchical Energy-based Reasoning for interpretable MEdical Scans (HERMES)
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
Structural Alignment for Network Pruning through Partial Regularization
A comprehensive survey of complex brain network representation
Bidirectional Mapping with Contrastive Learning on Multimodal Neuroimaging Data
Dietary supplementation with jasmine flower residue improves meat quality and flavor of goat
Interindividual Variability in Self-Monitoring of Blood Pressure Using Consumer-Purchased Wireless Devices
Decompose to Adapt: Cross-Domain Object Detection Via Feature Disentanglement
Learning multi-scale synergic discriminative features for prostate image segmentation
Signed graph representation learning for functional-to-structural brain network mapping
Towards bi-directional skip connections in encoder-decoder architectures and beyond
A Hierarchical Graph Learning Model for Brain Network Regression Analysis
Network Pruning via Performance Maximization
BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture
PDAM: A Panoptic-Level Feature Alignment Framework for Unsupervised Domain Adaptive Instance Segmentation in Microscopy Images
Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-Weighting
Deep Learning-Based Image Segmentation on Multimodal Medical Imaging
3D APA-Net: 3D Adversarial Pyramid Anisotropic Convolutional Network for Prostate Segmentation in MR Images
Improvement of a Deep Learning Algorithm for Total Electron Content Maps: Image Completion
Multiscale Kernels for Enhanced U-Shaped Network to Improve 3D Neuron Tracing
Multi-Pass Fast Watershed for Accurate Segmentation of Overlapping Cervical Cells
Panoptic Segmentation with an End-to-End Cell R-CNN for Pathology Image Analysis
Deep Learning Models Unveiled Functional Difference Between Cortical Gyri and Sulci
Bilevel Distance Metric Learning for Robust Image Recognition
Neural Information Processing Systems 2018cited by 23position: last
Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization
Optimizing the cervix cytological examination based on deep learning and dynamic shape modeling
Locally-Transferred Fisher Vectors for Texture Classification
Automatic segmentation of overlapping cervical smear cells based on local distinctive features and guided shape deformation
Large Margin Local Estimate With Applications to Medical Image Classification
Collaborative Research: FIRE-MODEL: Advanced AI Framework to Improve Understanding and Prediction of Wildland Fire
Collaborative Research: PPoSS: LARGE: Co-designing Hardware, Software, and Algorithms to Enable Extreme-Scale Machine Learning Systems
A New Machine Learning Framework for Single-Cell Multi-Omics Bioinformatics
SCH: INT: New Machine Learning Framework to Conduct Anesthesia Risk Stratification and Decision Support for Precision Health
BIGDATA: IA: Collaborative Research: Asynchronous Distributed Machine Learning Framework for Multi-Site Collaborative Brain Big Data Mining
III: Medium: Collaborative Research: Integrating Large-Scale Machine Learning and Edge Computing for Collaborative Autonomous Vehicles
Collaborative Research: CCRI: New: A Scalable Hardware and Software Environment Enabling Secure Multi-party Learning
Collaborative Research: III: Medium: New Machine Learning Empowered Nanoinformatics System for Advancing Nanomaterial Design
Collaborative Research: PPoSS: LARGE: Co-designing Hardware, Software, and Algorithms to Enable Extreme-Scale Machine Learning Systems
A New Machine Learning Framework for Single-Cell Multi-Omics Bioinformatics
Collaborative Research: CCRI: New: A Scalable Hardware and Software Environment Enabling Secure Multi-party Learning
Collaborative Research: III: Medium: New Machine Learning Empowered Nanoinformatics System for Advancing Nanomaterial Design
III: Medium: Collaborative Research: Integrating Large-Scale Machine Learning and Edge Computing for Collaborative Autonomous Vehicles
BIGDATA: IA: Collaborative Research: Asynchronous Distributed Machine Learning Framework for Multi-Site Collaborative Brain Big Data Mining
SCH: INT: New Machine Learning Framework to Conduct Anesthesia Risk Stratification and Decision Support for Precision Health
BIGDATA: Collaborative Research: IA: Big Imaging-Omics Data Mining Framework for Precision Medicine
III: Small: Robust Large-Scale Data Mining for Knowledge Discovery in Depression Thought Records
III: Medium: Collaborative Research: Robust Large-Scale Electronic Medical Record Data Mining Framework to Conduct Risk Stratification for Personalized Intervention
ABI Innovation: A New Automated Data Integration, Annotations, and Interaction Network Inference System for Analyzing Drosophila Gene Expression
SCH: EXP: Collaborative Research: Privacy-Preserving Framework for Publishing Electronic Healthcare Records
BIGDATA: Collaborative Research: IA: Big Imaging-Omics Data Mining Framework for Precision Medicine
III: Small: Robust Large-Scale Data Mining for Knowledge Discovery in Depression Thought Records
ABI Innovation: A New Automated Data Integration, Annotations, and Interaction Network Inference System for Analyzing Drosophila Gene Expression
SCH: EXP: Collaborative Research: Privacy-Preserving Framework for Publishing Electronic Healthcare Records
III: Medium: Collaborative Research: Robust Large-Scale Electronic Medical Record Data Mining Framework to Conduct Risk Stratification for Personalized Intervention