5 papers
ViM-Q: Scalable Algorithm-Hardware Co-Design for Vision Mamba Model Inference on FPGA
Shengzhe Lyu, Yuhan She, Patrick S. Y. Hung +2
Vision Mamba (ViM) models offer a compelling efficiency advantage over Transformers by leveraging the linear complexity of State Space Models (SSMs), yet efficiently deploying them…
SwiftChannel: Algorithm-Hardware Co-Design for Deep Learning-Based 5G Channel Estimation
Shengzhe Lyu, Yuhan She, Di Duan +5
Channel estimation is crucial in 5G communication networks for optimizing transmission parameters and ensuring reliable, high-speed communication. However, the use of multiple-inpu…
HHEML: Hybrid Homomorphic Encryption for Privacy-Preserving Machine Learning on Edge
Yu Hin Chan, Hao Yang, Shiyu Shen +4
Privacy-preserving machine learning (PPML) is an emerging topic to handle secure machine learning inference over sensitive data in untrusted environments. Fully homomorphic encrypt…
Argus: Multi-View Egocentric Human Mesh Reconstruction Based on Stripped-Down Wearable mmWave Add-on
Di Duan, Shengzhe Lyu, Mu Yuan +5
In this paper, we propose Argus, a wearable add-on system based on stripped-down (i.e., compact, lightweight, low-power, limited-capability) mmWave radars. It is the first to achie…
EarDA: Towards Accurate and Data-Efficient Earable Activity Sensing
Shengzhe Lyu, Yongliang Chen, Di Duan +2
In the realm of smart sensing with the Internet of Things, earable devices are empowered with the capability of multi-modality sensing and intelligence of context-aware computing,…