activity
20132026
most citedToward Open-World Electroencephalogram Decoding Via Deep Learning: A Comprehensive Survey

95 citations · 216 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2026

FCUS-rPPG: A Fast-Converging Unsupervised Framework for Remote Photoplethysmography via Gradient Oscillation Suppression

Jiajie Li, Yu Liu, Rencheng Song +2

Remote photoplethysmography (rPPG) enables non-contact extraction of blood volume pulse (BVP) signals using consumer-grade cameras. Recent unsupervised rPPG methods learn BVP repre…

cs.CV2026

Degradation-Robust Fusion: An Efficient Degradation-Aware Diffusion Framework for Multimodal Image Fusion in Arbitrary Degradation Scenarios

Yu Shi, Yu Liu, Zhong-Cheng Wu +3

Complex degradations like noise, blur, and low resolution are typical challenges in real world image fusion tasks, limiting the performance and practicality of existing methods. En…

cs.CV2025

EmoFeedback: Reinforcement of Continuous Emotional Image Generation via LVLM-based Reward and Textual Feedback

Kai Shu, Jingyang Jia, Gang Yang +3

Continuous emotional image content generation (C-EICG) is emerging rapidly due to its ability to produce images aligned with both user descriptions and continuous emotional values.…

cs.CV2024

Dual Graph Attention based Disentanglement Multiple Instance Learning for Brain Age Estimation

Fanzhe Yan, Gang Yang, Yu Li +2

Deep learning techniques have demonstrated great potential for accurately estimating brain age by analyzing Magnetic Resonance Imaging (MRI) data from healthy individuals. However,…

eess.SP2023★ 30 cited

Data Augmentation for Seizure Prediction with Generative Diffusion Model

Kai Shu, Le Wu, Yuchang Zhao +3

Data augmentation (DA) can significantly strengthen the electroencephalogram (EEG)-based seizure prediction methods. However, existing DA approaches are just the linear transformat…

cs.CV2023★ 2 cited

PanFlowNet: A Flow-Based Deep Network for Pan-sharpening

Gang Yang, Xiangyong Cao, Wenzhe Xiao +4

Pan-sharpening aims to generate a high-resolution multispectral (HRMS) image by integrating the spectral information of a low-resolution multispectral (LRMS) image with the texture…