Hyeongsu Kim

Hyeongsu Kim

Seoul National University

H-index: 8

Asia-South Korea

About Hyeongsu Kim

Hyeongsu Kim, With an exceptional h-index of 8 and a recent h-index of 8 (since 2020), a distinguished researcher at Seoul National University, specializes in the field of neuromorphic device.

His recent articles reflect a diverse array of research interests and contributions to the field:

Variation-Tolerant Capacitive Array for Binarized Neural Network

Novel method enabling forward and backward propagations in NAND flash memory for on-chip learning

NAND flash based novel synaptic architecture for highly robust and high-density quantized neural networks with binary neuron activation of (1, 0)

Efficient precise weight tuning protocol considering variation of the synaptic devices and target accuracy

Pruning for hardware-based deep spiking neural networks using gated schottky diode as synaptic devices

On-chip training spiking neural networks using approximated backpropagation with analog synaptic devices

Effect of word-line bias on linearity of multi-level conductance steps for multi-layer neural networks based on NAND flash cells

Hyeongsu Kim Information

University

Position

___

Citations(all)

314

Citations(since 2020)

313

Cited By

101

hIndex(all)

8

hIndex(since 2020)

8

i10Index(all)

8

i10Index(since 2020)

8

Email

University Profile Page

Seoul National University

Google Scholar

View Google Scholar Profile

Hyeongsu Kim Skills & Research Interests

neuromorphic device

Top articles of Hyeongsu Kim

Title

Journal

Author(s)

Publication Date

Variation-Tolerant Capacitive Array for Binarized Neural Network

IEEE Electron Device Letters

Hyeongsu Kim

Sung Yun Woo

Soochang Lee

Young-Tak Seo

Byung-Gook Park

...

2022/1/14

Novel method enabling forward and backward propagations in NAND flash memory for on-chip learning

IEEE Transactions on Electron Devices

Sung-Tae Lee

Gyuho Yeom

Honam Yoo

Hyeong-Su Kim

Suhwan Lim

...

2021/5/27

NAND flash based novel synaptic architecture for highly robust and high-density quantized neural networks with binary neuron activation of (1, 0)

IEEE Access

Sung-Tae Lee

Dongseok Kwon

Hyeongsu Kim

Honam Yoo

Jong-Ho Lee

2020/6/22

Efficient precise weight tuning protocol considering variation of the synaptic devices and target accuracy

Neurocomputing

Hyeongsu Kim

Jong-Ho Bae

Suhwan Lim

Sung-Tae Lee

Young-Tak Seo

...

2020/2/22

Pruning for hardware-based deep spiking neural networks using gated schottky diode as synaptic devices

Journal of Nanoscience and Nanotechnology

Sung-Tae Lee

Suhwan Lim

Jong-Ho Bae

Dongseok Kwon

Hyeong-Su Kim

...

2020/11/1

On-chip training spiking neural networks using approximated backpropagation with analog synaptic devices

Frontiers in neuroscience

Dongseok Kwon

Suhwan Lim

Jong-Ho Bae

Sung-Tae Lee

Hyeongsu Kim

...

2020/7/7

Effect of word-line bias on linearity of multi-level conductance steps for multi-layer neural networks based on NAND flash cells

Journal of Nanoscience and Nanotechnology

Sung-Tae Lee

Suhwan Lim

Nagyong Choi

Jong-Ho Bae

Dongseok Kwon

...

2020/7/1

See List of Professors in Hyeongsu Kim University(Seoul National University)