papers

Publications (10)

cs.CV2023

Towards Open-set Gesture Recognition via Feature Activation Enhancement and Orthogonal Prototype Learning

Chen Liu, Can Han, Chengfeng Zhou +4

Gesture recognition is a foundational task in human-machine interaction (HMI). While there has been significant progress in gesture recognition based on surface electromyography (s…

cs.HC2026

EMGFlow: Robust and Efficient Surface Electromyography Synthesis via Flow Matching

Boxuan Jiang, Chenyun Dai, Can Han

Deep learning-based surface electromyography (sEMG) gesture recognition is frequently bottlenecked by data scarcity and limited subject diversity. While synthetic data generation v…

cs.HC2024

A Spatial-Spectral and Temporal Dual Prototype Network for Motor Imagery Brain-Computer Interface

Can Han, Chen Liu, Yaqi Wang +3

Motor imagery electroencephalogram (MI-EEG) decoding plays a crucial role in developing motor imagery brain-computer interfaces (MI-BCIs). However, decoding intentions from MI rema…

cs.CV2026

SASG-DA: Sparse-Aware Semantic-Guided Diffusion Augmentation For Myoelectric Gesture Recognition

Chen Liu, Can Han, Weishi Xu +2

Surface electromyography (sEMG)-based gesture recognition plays a critical role in human-machine interaction (HMI), particularly for rehabilitation and prosthetic control. However,…

eess.IV2025

MICCAI STS 2024 Challenge: Semi-Supervised Instance-Level Tooth Segmentation in Panoramic X-ray and CBCT Images

Yaqi Wang, Zhi Li, Chengyu Wu +19

Orthopantomogram (OPGs) and Cone-Beam Computed Tomography (CBCT) are vital for dentistry, but creating large datasets for automated tooth segmentation is hindered by the labor-inte…

cs.CV2025

MICCAI STSR 2025 Challenge: Semi-Supervised Teeth and Pulp Segmentation and CBCT-IOS Registration

Yaqi Wang, Zhi Li, Chengyu Wu +15

Cone-Beam Computed Tomography (CBCT) and Intraoral Scanning (IOS) are essential for digital dentistry, but annotated data scarcity limits automated solutions for pulp canal segment…

cs.LG2026

Angular Gaussian Supervised Contrastive Learning for Long-Tailed Electrocardiogram Arrhythmia Diagnosis

Jin Dai, Qiuzhen Zhang, Chenyun Dai +2

The paper introduces Angular Gaussian Supervised Contrastive Learning (AG‑SCL), a method that combines anisotropic contrastive embeddings, adaptive logit adjustment, and tail‑aware…

#electrocardiogram#arrhythmia detection#long-tailed learning#contrastive learning
cs.CV2024

Towards Open-Set Myoelectric Gesture Recognition via Dual-Perspective Inconsistency Learning

Chen Liu, Can Han, Chengfeng Zhou +2

Gesture recognition based on surface electromyography (sEMG) has achieved significant progress in human-machine interaction (HMI), especially in prosthetic control and movement reh…

cs.HC2026

Fusion of Spatio-Temporal and Multi-Scale Frequency Features for Dry Electrodes MI-EEG Decoding

Tianyi Gong, Can Han, Junxi Wu +1

Dry-electrode Motor Imagery Electroencephalography (MI-EEG) enables fast, comfortable, real-world Brain Computer Interface by eliminating gels and shortening setup for at-home and…

eess.IV2025

Robust Real-Time Endoscopic Stereo Matching under Fuzzy Tissue Boundaries

Yang Ding, Can Han, Sijia Du +2

Real-time acquisition of accurate scene depth is essential for automated robotic minimally invasive surgery. Stereo matching with binocular endoscopy can provide this depth informa…