관심 주제를 입력하면 그 주제의 논문을 낸 연구실을 관련도 순으로 보여드려요. 순위가 아니라 근거 논문과 함께 보는 출발점이에요.
2026 논문이 아직 반영되지 않은 연구실은 결과에서 불리할 수 있어요.
Efficient Brain-to-Speech Decoding with Fixed-Delay Spiking Neural Networks
A. Wisniewska, S.-H. Lee, S.-W. Lee
KU이성환
Hyunho Kook, Byeongho Yu, Jeongmin Oh, Eunhyeok Park
POSTECH김동우, 옥정슬, 박상돈, 박은혁
NeuLPU: A 3.6 mW Spiking LLM Processing Unit for On-device Long-context Inference
S. Lee, S. Ha, S. Kim, W. Jo, Sangyeob Kim, Hoi-jun yoo
Yonsei김상엽
C-Transformer: A Homogeneous DNN-Transformer/Spiking-Transformer Processor for Large-Language-Models
Sangyeob Kim, S.Kim, W.Jo, S.Kim, S.Hong, N.Lee, J.Lee, Hoi-Jun Yoo
Yonsei김상엽
In-cell neuromorphic computing in solid oxide fuel cells for bifunctional electrochemical power generation and artificial intelligence
Haewon Seo, Min-Kyu Song, Hyun Woo Ko, Ji-Hoon Kang, Giho Lee, SunYoung Park, Hyunwoo J. Kim, Sungchul Mun, Jeehwan Kim, Min-Chul Park, and Kyung Joong Yoon
KAIST김현우
Neuromorphic olfaction with ultralow-power gas sensors and ovonic threshold switch
Mingu Kang, Joon-Kyuu Han, Kichul Lee, Jaeseok Jeong, Chanyoung Yoo, Jeong Woo Jeon, Byongwoo Park, Wonho Choi, Junseong Ahn, Kuk-Jin Yoon, Cheol Seong Hwang, Inkyu Park
KAIST윤국진
C-Transformer: A 2.6-18.1μJ/Token Homogeneous DNN-Transformer/Spiking-Transformer Processor with Big-Little Network and Implicit Weight Generation for Large Language Models
Sangyeob Kim, S.Kim, W.Jo, S.kim, S.Hong, Hoi-Jun Yoo
Yonsei김상엽
Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network
Hyunseok Oh, Youngki Lee
SNU이영기
DualNet: Efficient Integration of Artificial Neural Network and Spiking Neural Network with Equivalent Conversion
S.Hong, Sangyeob Kim, S.Kim, Hoi-Jun Yoo
Yonsei김상엽
Simultaneous Spike Processing for 3D NAND-Based Spiking Neural Networks
Bosung Jeon, Seunghwan Song, Jae-Joon Kim, Woo Young Choi
SNU김재준
C-DNN: A 24.5-85.8TOPS/W Complementary-Deep-Neural-Network Processor with Heterogeneous CNN/SNN Core Architecture and Forward-Gradient-Based Sparsity Generation
Sangyeob Kim, S.Kim, S.Hong, S.Kim, D.Han, Hoi-Jun Yoo
Yonsei김상엽
C-DNN: An Energy-Efficient Complementary Deep-Neural-Network Processor With Heterogeneous CNN/SNN Core Architecture
Sangyeob Kim, S.Kim, S.Hong, S.Kim, D.Han, J.Choi, Hoi-Jun Yoo
Yonsei김상엽
Neuro-CIM: ADC-Less Neuromorphic Computing-in-Memory Processor With Operation Gating/Stopping and Digital–Analog Networks
Sangyeob Kim, S.Kim, S.Um, S.Kim, K.Kim, Hoi-Jun Yoo
Yonsei김상엽
Multi-Objective Architecture Search and Optimization for Heterogeneous Neuromorphic Architecture
Juseong Park, Yongwon Shin, Hyojin Sung
SNU성효진
A Reconfigurable 1T1C eDRAM-based Spiking Neural Network Computing-In-Memory Processor for High System-Level Efficiency
S.Kim, S.Kim, S.Um, S.Kim, Z.Li, Sangyeob Kim, W. Jo, Hoi-Jun Yoo
Yonsei김상엽
A 65nm 12.92nJ/inference Mixed-Signal Neuromorphic Processor for Image Classification
Y. Ko, S. Kim, K. Shin, Y. Park, S. Kim, and D. Jeon
SNU전동석
A Resource-Efficient Super-Resolution FPGA Processor with Heterogeneous CNN and SNN Core Architecture
J.Choi, Sangyeob Kim, W.Park, W.Jo, Hoi-Jun Yoo
Yonsei김상엽
COOL-NPU: Complementary Online Learning Neural Processing Unit with CNN-SNN Heterogeneous Core and Event-driven Backpropagation
Sangyeob Kim, S.Kim, S.Hong, S.Kim, D.Han, J.Choi, Hoi-Jun Yoo
Yonsei김상엽
Efficient Convolutional Processing of Spiking Neural Network with Weight-Sharing Filters
Seunghwan Song, Bosung Jeon, Munhyeon Kim, Jae-Joon Kim
SNU김재준