BRIEDGE: EEG-Adaptive Edge AI for Multi-Brain to Multi-Robot Interaction

no code implementations • 14 Mar 2024 • Jinhui Ouyang, Mingzhu Wu, Xinglin Li, Hanhui Deng, Di wu

To better extract the joint features of heterogeneous EEG data as well as enhance classification accuracy, BRIEDGE introduces an informer-based ProbSparse self-attention mechanism.

EEG Model Compression +1

Attend Who is Weak: Enhancing Graph Condensation via Cross-Free Adversarial Training

no code implementations • 27 Nov 2023 • Xinglin Li, Kun Wang, Hanhui Deng, Yuxuan Liang, Di wu

We seminally propose the concept of Shock Absorber (a type of perturbation) that enhances the robustness and stability of the original graphs against changes in an adversarial training fashion.

Node Classification

ToThePoint: Efficient Contrastive Learning of 3D Point Clouds via Recycling

no code implementations • CVPR 2023 • Xinglin Li, Jiajing Chen, Jinhui Ouyang, Hanhui Deng, Senem Velipasalar, Di wu

Recent years have witnessed significant developments in point cloud processing, including classification and segmentation.

Contrastive Learning Self-Supervised Learning

Software-Defined Edge Computing: A New Architecture Paradigm to Support IoT Data Analysis

no code implementations • 22 Apr 2021 • Di wu, XiaoFeng Xie, Xiang Ni, Bin Fu, Hanhui Deng, Haibo Zeng, Zhijin Qin

We further present an experiment on data anomaly detection in this architecture, and the comparison between two architectures for ECG diagnosis.

Anomaly Detection Edge-computing