activity
20202026
most citedGCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery Signals

180 citations · 214 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications

Arif Hassan Zidan, Yi Pan, Hanqi Jiang +23

World models, internal simulators that learn the structure and dynamics of an environment, have emerged as a central paradigm in the pursuit of artificial general intelligence, ena…

cs.CV2026

MedVIGIL: Evaluating Trustworthy Medical VLMs Under Broken Visual Evidence

Hanqi Jiang, Junhao Chen, Mingyu Kang +12

Medical vision--language models (VLMs) are usually evaluated on intact image--question pairs, but trustworthy clinical use requires a stronger property: a model must recognise when…

q-bio.NC2025

Voxel-Level Brain States Prediction Using Swin Transformer

Yifei Sun, Daniel Chahine, Qinghao Wen +5

Understanding brain dynamics is important for neuroscience and mental health. Functional magnetic resonance imaging (fMRI) enables the measurement of neural activities through bloo…

cs.CV2025★ 2 cited

Towards a general-purpose foundation model for fMRI analysis

Cheng Wang, Yu Jiang, Zhihao Peng +18

Functional MRI (fMRI) is crucial for studying brain function and diagnosing neurological disorders. However, existing analysis methods suffer from reproducibility and transferabili…

eess.SP2020★ 180 cited

GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery Signals

Yimin Hou, Shuyue Jia, Xiangmin Lun +5

Towards developing effective and efficient brain-computer interface (BCI) systems, precise decoding of brain activity measured by electroencephalogram (EEG), is highly demanded. Tr…

eess.SP2020★ 32 cited

Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition

Yimin Hou, Shuyue Jia, Xiangmin Lun +4

Recognition accuracy and response time are both critically essential ahead of building practical electroencephalography (EEG) based brain-computer interface (BCI). Recent approache…