15 citations · 19 across the 6 of their papers we have counts for
6 papers
Improving Multiple Sclerosis Lesion Segmentation Across Clinical Sites: A Federated Learning Approach with Noise-Resilient Training
Lei Bai, Dongang Wang, Michael Barnett +13
Accurately measuring the evolution of Multiple Sclerosis (MS) with magnetic resonance imaging (MRI) critically informs understanding of disease progression and helps to direct ther…
Learning from pseudo-labels: deep networks improve consistency in longitudinal brain volume estimation
Geng Zhan, Dongang Wang, Mariano Cabezas +5
Brain atrophy is an important biomarker for monitoring neurodegeneration and disease progression in conditions such as multiple sclerosis (MS). An accurate and robust quantitative…
MS Lesion Segmentation: Revisiting Weighting Mechanisms for Federated Learning
Dongnan Liu, Mariano Cabezas, Dongang Wang +16
Federated learning (FL) has been widely employed for medical image analysis to facilitate multi-client collaborative learning without sharing raw data. Despite great success, FL's…
Scope Head for Accurate Localization in Object Detection
Geng Zhan, Dan Xu, Guo Lu +3
Existing anchor-based and anchor-free object detectors in multi-stage or one-stage pipelines have achieved very promising detection performance. However, they still encounter the d…
Dynamic Spatial-Temporal Representation Learning for Traffic Flow Prediction
Lingbo Liu, Jiajie Zhen, Guanbin Li +4
As a crucial component in intelligent transportation systems, traffic flow prediction has recently attracted widespread research interest in the field of artificial intelligence (A…
Extended Local Binary Patterns for Efficient and Robust Spontaneous Facial Micro-Expression Recognition
Chengyu Guo, Jingyun Liang, Geng Zhan +3
Facial Micro-Expressions (MEs) are spontaneous, involuntary facial movements when a person experiences an emotion but deliberately or unconsciously attempts to conceal his or her g…