14.6 A 1.42TOPS/W deep convolutional neural network recognition processor for intelligent IoE systems. - Jaehyeong Sim; Jun-Seok Park; Minhye Kim; Dongmyung Bae; Yeongjae Choi; Lee-Sup Kim (ISSCC, 2016)

A Kernel Decomposition Architecture for Binary-weight Convolutional Neural Networks. - Hyeonuk Kim; Jaehyeong Sim; Yeongjae Choi; Lee-Sup Kim (DAC, 2017)

Hardware-Centric Vision Processing for Mobile IoT Environment Exploiting Approximate Graph Cut in Resistor Grid. - Yeongjae Choi; Jun-Seok Park; Lee-Sup Kim (WACV, 2017)

Energy-Efficient Design of Processing Element for Convolutional Neural Network. - Yeongjae Choi; Dongmyung Bae; Jaehyeong Sim; Seungkyu Choi; Minhye Kim; Lee-Sup Kim (IEEE Trans. Circuits Syst. II Express Briefs, 2017)

A 47.4µJ/epoch Trainable Deep Convolutional Neural Network Accelerator for In-Situ Personalization on Smart Devices. - Seungkyu Choi; Jaehyeong Sim; Myeonggu Kang; Yeongjae Choi; Hyeonuk Kim; Lee-Sup Kim (A-SSCC, 2019)

An Optimized Design Technique of Low-bit Neural Network Training for Personalization on IoT Devices. - Seungkyu Choi; Jaekang Shin; Yeongjae Choi; Lee-Sup Kim (DAC, 2019)

NAND-Net: Minimizing Computational Complexity of In-Memory Processing for Binary Neural Networks. - Hyeonuk Kim; Jaehyeong Sim; Yeongjae Choi; Lee-Sup Kim (HPCA, 2019)

eSRCNN: A Framework for Optimizing Super-Resolution Tasks on Diverse Embedded CNN Accelerators. - Youngbeom Jung; Yeongjae Choi; Jaehyeong Sim; Lee-Sup Kim (ICCAD, 2019)

A Pragmatic Approach to On-device Incremental Learning System with Selective Weight Updates. - Jaekang Shin; Seungkyu Choi; Yeongjae Choi; Lee-Sup Kim (DAC, 2020)

An Energy-Efficient Deep Convolutional Neural Network Training Accelerator for In Situ Personalization on Smart Devices. - Seungkyu Choi; Jaehyeong Sim; Myeonggu Kang; Yeongjae Choi; Hyeonuk Kim; Lee-Sup Kim (IEEE J. Solid State Circuits, 2020)

CREMON: Cryptography Embedded on the Convolutional Neural Network Accelerator. - Yeongjae Choi; Jaehyeong Sim; Lee-Sup Kim (IEEE Trans. Circuits Syst., 2020)

Sparsity-Aware and Re-configurable NPU Architecture for Samsung Flagship Mobile SoC. - Jun-Woo Jang; Sehwan Lee; Dongyoung Kim; Hyunsun Park; Ali Shafiee Ardestani; Yeongjae Choi; Channoh Kim; Yoojin Kim; Hyeongseok Yu; Hamzah Abdel-Aziz; Jun-Seok Park; Heonsoo Lee; et al. (ISCA, 2021)

Driver Drowsiness Detection based on 3D Convolution Neural Network with Optimized Window Size. - Namkyoo Kang; Seungeun Han; Seungyeon Kim 004; SeungJoon Kwon; Yeongjae Choi; Yong-Tae Lee; Seung-Ik Lee (ICTC, 2022)

Rare Computing: Removing Redundant Multiplications From Sparse and Repetitive Data in Deep Neural Networks. - Kangkyu Park; Seungkyu Choi; Yeongjae Choi; Lee-Sup Kim (IEEE Trans. Computers, 2022)

Quantization-Error-Robust Deep Neural Network for Embedded Accelerators. - Youngbeom Jung; Hyeonuk Kim; Yeongjae Choi; Lee-Sup Kim (IEEE Trans. Circuits Syst. II Express Briefs, 2022)