Yonggan Fu

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20212025

most citedHW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark

24 citations · 72 across the 20 of their papers we have counts for

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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…

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