Fixed-Point Quantization of 3D Convolutional Neural Networks for Energy-Efficient Action Recognition. - Hyunhoon Lee; Younghoon Byun; Seokha Hwang; Sunggu Lee; Youngjoo Lee (ISOCC, 2018)

FPGA-Based Sparsity-Aware CNN Accelerator for Noise-Resilient Edge-Level Image Recognition. - Seungsik Moon; Hyunhoon Lee; Younghoon Byun; Jongmin Park; Junseo Joe; Seokha Hwang; Sunggu Lee; Youngjoo Lee (A-SSCC, 2019)

Low-Cost Network Scheduling of 3D-CNN Processing for Embedded Action Recognition. - Hyunhoon Lee; Young-Seok Kim; Mijung Kim; Youngjoo Lee (IEEE Access, 2021)

Fast Estimation of NTT/INTT Accelerator Costs for RNS-Based Homomorphic Encryption. - Gyuhyun Jung; Hyeokjun Kwon; Hyunhoon Lee; Youngjoo Lee (ISOCC, 2022)

Optimizations of Privacy-Preserving DNN for Low-Latency Inference on Encrypted Data. - Hyunhoon Lee; Youngjoo Lee (IEEE Access, 2023)

16.1 A 2.7-to-13.3μJ/boot/slot Flexible RNS-CKKS Processor in 28nm CMOS Technology for FHE-Based Privacy-Preserving Computing. - Hyunhoon Lee; Hyeokjun Kwon; Youngjoo Lee (ISSCC, 2024)

Energy-Efficient Flexible RNS-CKKS Processor for FHE-Based Privacy-Preserving Computing. - Hyeokjun Kwon; Hyunhoon Lee; Gyuhyun Jung; Youngjoo Lee (IEEE J. Solid State Circuits, 2025)