Shang Wu

most citede-G2C: A 0.14-to-8.31

μ

J/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM

4 citations · 4 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2023

NetDistiller: Empowering Tiny Deep Learning via In-Situ Distillation

Shunyao Zhang, Yonggan Fu, Shang Wu +4

Boosting the task accuracy of tiny neural networks (TNNs) has become a fundamental challenge for enabling the deployments of TNNs on edge devices which are constrained by strict li…

eess.SP2022★ 4 cited

e-G2C: A 0.14-to-8.31 $μ$ J/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM

Yang Zhao, Yongan Zhang, Yonggan Fu +10

This work presents the first silicon-validated dedicated EGM-to-ECG (G2C) processor, dubbed e-G2C, featuring continuous lightweight anomaly detection, event-driven coarse/precise c…

NetDistiller: Empowering Tiny Deep Learning via In-Situ Distillation

e-G2C: A 0.14-to-8.31 μJ/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM

e-G2C: A 0.14-to-8.31 $μ$ J/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM