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Hyun Kim 0001
Person information
- affiliation: Seoul National University of Science and Technology, Department of Electrical and Information Engineering, Seoul, South Korea
Other persons with the same name
- Hyun Kim — disambiguation page
- Hyun Kim 0002
— Yonsei University, Department of Biomedical Engineering College of Health Science, Seoul, South Korea
- Hyun Kim 0003
— Pohang University of Science and Technology, Pohang, South Korea
- Hyun Kim 0004
— Boston Children's Hospital, Boston, MA, USA
- Hyun Kim 0005
— Korea University, Department of Physics, Seoul, South Korea
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2020 – today
- 2025
- [j34]Seung-Hwan Bae, Hyuk-Jae Lee
, Hyun Kim
:
MCM-SR: Multiple Constant Multiplication-Based CNN Streaming Hardware Architecture for Super-Resolution. IEEE Trans. Very Large Scale Integr. Syst. 33(1): 75-87 (2025) - 2024
- [j33]Jongho Lee, Hyun Kim
:
DCT-ViT: High-Frequency Pruned Vision Transformer With Discrete Cosine Transform. IEEE Access 12: 80386-80396 (2024) - [j32]Dahun Choi, Juntae Park, Hyun Kim
:
HLQ: Hardware-Friendly Logarithmic Quantization Aware Training for Power-Efficient Low-Precision CNN Models. IEEE Access 12: 159611-159621 (2024) - [j31]Hyeonseok Hong, Dahun Choi, Namjoon Kim, Haein Lee, Beom Jin Kang, Huibeom Kang, Hyun Kim:
Survey of convolutional neural network accelerators on field-programmable gate array platforms: architectures and optimization techniques. J. Real Time Image Process. 21(3): 64 (2024) - [j30]Beom Jin Kang, Haein Lee, Seok Kyu Yoon, Young Chan Kim, Sangbeom Jeong, Seong Jun O, Hyun Kim
:
A survey of FPGA and ASIC designs for transformer inference acceleration and optimization. J. Syst. Archit. 155: 103247 (2024) - [j29]Hyeonseok Hong, Dahun Choi, Namjoon Kim
, Hyun Kim
:
Mobile-X: Dedicated FPGA Implementation of the MobileNet Accelerator Optimizing Depthwise Separable Convolution. IEEE Trans. Circuits Syst. II Express Briefs 71(11): 4668-4672 (2024) - [j28]Nam Joon Kim
, Hyun Kim
:
Trunk Pruning: Highly Compatible Channel Pruning for Convolutional Neural Networks Without Fine-Tuning. IEEE Trans. Multim. 26: 5588-5599 (2024) - [j27]Dayoung Chun
, Seungil Lee, Hyun Kim
:
USD: Uncertainty-Based One-Phase Learning to Enhance Pseudo-Label Reliability for Semi-Supervised Object Detection. IEEE Trans. Multim. 26: 6336-6347 (2024) - [c32]Dayoung Chun, Hyuk-Jae Lee, Hyun Kim:
PF-Training: Parameter Freezing for Efficient On-Device Training of CNN-based Object Detectors in Low-Resource Environments. AICAS 2024: 21-25 - [c31]Inseong Hwang, Jihoon Jang, Hyun Kim:
An Architecture-Level Framework for Enabling Processing-Using-Memory Simulations in Deep Neural Networks. ICEIC 2024: 1-3 - [c30]Kwanghyun Koo, Hyun Kim:
Extreme Pruning Technique Based on Filter Deactivation Using Sparsity Training for Deep Convolutional Neural Networks. ICEIC 2024: 1-4 - [c29]Nam Joon Kim, Jongho Lee, Hyun Kim:
HyQ: Hardware-Friendly Post-Training Quantization for CNN-Transformer Hybrid Networks. IJCAI 2024: 4291-4299 - [c28]Jihoon Jang
, Hyokeun Lee
, Hyun Kim
:
EDeN: Enabling Low-Power CNN Inference on Edge Devices Using Prefetcher-assisted NVM Systems. ISLPED 2024: 1-6 - [c27]Beom Jin Kang, Nam Joon Kim, Hyun Kim:
Hardware-aware Network Compression for Hybrid Vision Transformer via Low-Rank Approximation. ISOCC 2024: 171-172 - 2023
- [j26]Dayoung Chun, Jiwoong Choi, Hyuk-Jae Lee
, Hyun Kim
:
CP-CNN: Computational Parallelization of CNN-Based Object Detectors in Heterogeneous Embedded Systems for Autonomous Driving. IEEE Access 11: 52812-52823 (2023) - [j25]Kwanghyun Koo, Hyun Kim
:
V-SKP: Vectorized Kernel-Based Structured Kernel Pruning for Accelerating Deep Convolutional Neural Networks. IEEE Access 11: 118547-118557 (2023) - [j24]Jeongjun Lee
, Hyun Kim
:
Multi-Step Training Framework Using Sparsity Training for Efficient Utilization of Accumulated New Data in Convolutional Neural Networks. IEEE Access 11: 129613-129622 (2023) - [j23]Hyokeun Lee
, Seungyong Lee, Byeongki Song, Moonsoo Kim, Seokbo Shim, Hyuk-Jae Lee
, Hyun Kim
:
An In-Module Disturbance Barrier for Mitigating Write Disturbance in Phase-Change Memory. IEEE Trans. Computers 72(4): 1150-1162 (2023) - [j22]Subin Ki, Juntae Park, Hyun Kim
:
Dedicated FPGA Implementation of the Gaussian TinyYOLOv3 Accelerator. IEEE Trans. Circuits Syst. II Express Briefs 70(10): 3882-3886 (2023) - [j21]Nam Joon Kim, Hyun Kim
:
FP-AGL: Filter Pruning With Adaptive Gradient Learning for Accelerating Deep Convolutional Neural Networks. IEEE Trans. Multim. 25: 5279-5290 (2023) - [c26]Kwanghyun Koo, Hyun Kim:
PPT-KP: Pruning Point Training-based Kernel Pruning for Deep Convolutional Neural Networks. AICAS 2023: 1-5 - [c25]Gilha Lee, Nam Joon Kim, Hyun Kim:
GPIL: Gradient with PseudoInverse Learning for High Accuracy Fine-Tuning. AICAS 2023: 1-5 - [c24]Jihoon Jang
, Hyun Kim, Hyokeun Lee:
Characterizing Memory Access Patterns of Various Convolutional Neural Networks for Utilizing Processing-in-Memory. ICEIC 2023: 1-3 - [c23]Nam Joon Kim, Hyun Kim:
AGT: Channel Pruning Using Adaptive Gradient Training for Accelerating Convolutional Neural Networks. ICEIC 2023: 1-3 - [c22]Seungil Lee, Hyun Kim, Dayoung Chun:
UCR-SSL: Uncertainty-Based Consistency Regularization for Semi-Supervised Learning. ICEIC 2023: 1-3 - [c21]Nam Joon Kim, Hyun Kim:
RepSGD: Channel Pruning Using Reparamerization for Accelerating Convolutional Neural Networks. ISCAS 2023: 1-5 - [c20]Beom Jin Kang, Nam Joon Kim, Jong Ho Lee, Hyun Kim:
Hardware-friendly Activation Functions for HybridViT Models. ISOCC 2023: 147-148 - 2022
- [j20]Moonsoo Kim, Hyokeun Lee
, Hyun Kim
, Hyuk-Jae Lee
:
WL-WD: Wear-Leveling Solution to Mitigate Write Disturbance Errors for Phase-Change Memory. IEEE Access 10: 11420-11431 (2022) - [c19]Subin Ki, Hyun Kim:
Activation Distribution-based Layer-wise Quantization for Convolutional Neural Networks. ICEIC 2022: 1-4 - [c18]Jihoon Jang
, Hyun Kim, Hyokeun Lee:
Performance Analysis of a Phase-Change Memory System on Various CNN Inference Workloads. ISOCC 2022: 133-134 - [c17]Hyokeun Lee
, Hyungsuk Kim, Seokbo Shim, Seungyong Lee, Do-sun Hong, Hyuk-Jae Lee, Hyun Kim:
PCMCsim: An Accurate Phase-Change Memory Controller Simulator and its Performance Analysis. ISPASS 2022: 300-310 - 2021
- [j19]Sungrae Kim
, Hyun Kim
:
Zero-Centered Fixed-Point Quantization With Iterative Retraining for Deep Convolutional Neural Network-Based Object Detectors. IEEE Access 9: 20828-20839 (2021) - [j18]Jin Shin
, Hyun Kim
:
RL-SPIHT: Reinforcement Learning-Based Adaptive Selection of Compression Ratios for 1-D SPIHT Algorithm. IEEE Access 9: 82485-82496 (2021) - [j17]Jeongjun Lee
, Jihoon Jang
, Jinhong Lee, Dayoung Chun, Hyun Kim
:
CNN-Based Mask-Pose Fusion for Detecting Specific Persons on Heterogeneous Embedded Systems. IEEE Access 9: 120358-120366 (2021) - [j16]Duy Thanh Nguyen
, Hyun Kim
, Hyuk-Jae Lee
:
Layer-Specific Optimization for Mixed Data Flow With Mixed Precision in FPGA Design for CNN-Based Object Detectors. IEEE Trans. Circuits Syst. Video Technol. 31(6): 2450-2464 (2021) - [c16]Seung-Hwan Bae, Hyuk-Jae Lee, Hyun Kim:
DC-AC: Deep Correlation-Based Adaptive Compression of Feature Map Planes in Convolutional Neural Networks. ISCAS 2021: 1-5 - [c15]Seung-Hwan Bae, Hyuk-Jae Lee, Hyun Kim:
Cache Compression with Golomb-Rice Code and Quantization for Convolutional Neural Networks. ISCAS 2021: 1-5 - 2020
- [j15]Duy Thanh Nguyen
, Huy Hung Nguyen, Hyun Kim
, Hyuk-Jae Lee
:
An Approximate Memory Architecture for Energy Saving in Deep Learning Applications. IEEE Trans. Circuits Syst. I Fundam. Theory Appl. 67-I(5): 1588-1601 (2020) - [j14]Xuan Truong Nguyen
, Hyun Kim
, Hyuk-Jae Lee
:
An Efficient Sampling Algorithm With a K-NN Expanding Operator for Depth Data Acquisition in a LiDAR System. IEEE Trans. Circuits Syst. Video Technol. 30(12): 4700-4714 (2020) - [j13]Jin Woo Park
, Hyokeun Lee
, Boyeal Kim
, Dong-Goo Kang
, Seung Oh Jin, Hyun Kim
, Hyuk-Jae Lee
:
A Low-Cost and High-Throughput FPGA Implementation of the Retinex Algorithm for Real-Time Video Enhancement. IEEE Trans. Very Large Scale Integr. Syst. 28(1): 101-114 (2020) - [c14]Jiwoong Choi
, Dayoung Chun, Hyuk-Jae Lee, Hyun Kim:
Uncertainty-based Object Detector for Autonomous Driving Embedded Platforms. AICAS 2020: 16-20 - [c13]Boyeal Kim, Sang Hyun Lee, Hyun Kim, Duy Thanh Nguyen, Minh-Son Le, Ik Joon Chang, Dohun Kwon, Jin Hyeok Yoo, Jun Won Choi, Hyuk-Jae Lee:
PCM: Precision-Controlled Memory System for Energy Efficient Deep Neural Network Training. DATE 2020: 1199-1204 - [c12]Quan-Dung Pham, Xuan Truong Nguyen, Hyuk-Jae Lee, Hyun Kim:
An MAE-aware ROI Sampling Model for LiDAR. ISOCC 2020: 276-277 - [c11]Nam Joon Kim, Hyun Kim:
Mask-Soft Filter Pruning for Lightweight CNN Inference. ISOCC 2020: 316-317 - [i3]Duy Thanh Nguyen, Hyun Kim, Hyuk-Jae Lee:
Layer-specific Optimization for Mixed Data Flow with Mixed Precision in FPGA Design for CNN-based Object Detectors. CoRR abs/2009.01588 (2020) - [i2]Hyokeun Lee, Seungyong Lee, Byeongki Song, Moonsoo Kim, Seokbo Shim, Hyun Kim, Hyuk-Jae Lee:
Mitigating Write Disturbance Errors of Phase-Change Memory as In-Module Approach. CoRR abs/2011.00448 (2020)
2010 – 2019
- 2019
- [j12]Xuan Truong Nguyen, Khac-Thai Nguyen, Hyuk-Jae Lee, Hyun Kim
:
ROI-Based LiDAR Sampling Algorithm in on-Road Environment for Autonomous Driving. IEEE Access 7: 90243-90253 (2019) - [j11]Moonsoo Kim
, Jungwoo Choi, Hyun Kim
, Hyuk-Jae Lee
:
An Effective DRAM Address Remapping for Mitigating Rowhammer Errors. IEEE Trans. Computers 68(10): 1428-1441 (2019) - [j10]Hyokeun Lee
, Moonsoo Kim, Hyunchul Kim, Hyun Kim, Hyuk-Jae Lee:
Integration and Boost of a Read-Modify-Write Module in Phase Change Memory System. IEEE Trans. Computers 68(12): 1772-1784 (2019) - [j9]Jiwoong Choi
, Boyeal Kim
, Hyun Kim
, Hyuk-Jae Lee
:
A High-Throughput Hardware Accelerator for Lossless Compression of a DDR4 Command Trace. IEEE Trans. Very Large Scale Integr. Syst. 27(1): 92-102 (2019) - [j8]Duy Thanh Nguyen
, Tuan Nghia Nguyen
, Hyun Kim
, Hyuk-Jae Lee
:
A High-Throughput and Power-Efficient FPGA Implementation of YOLO CNN for Object Detection. IEEE Trans. Very Large Scale Integr. Syst. 27(8): 1861-1873 (2019) - [c10]Xuan Truong Nguyen, Jiwoong Choi
, Hyuk-Jae Lee, Hyun Kim:
A Hardware-Friendly Compression Algorithm for Profiling DDR4 Memory Accesses. ICEIC 2019: 1-2 - [c9]Jiwoong Choi
, Dayoung Chun, Hyun Kim, Hyuk-Jae Lee:
Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving. ICCV 2019: 502-511 - [i1]Jiwoong Choi, Dayoung Chun, Hyun Kim, Hyuk-Jae Lee:
Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving. CoRR abs/1904.04620 (2019) - 2018
- [j7]Hyun Kim
, Ik Joon Chang
, Hyuk-Jae Lee
:
Optimal Selection of SRAM Bit-Cell Size for Power Reduction in Video Compression. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(3): 431-443 (2018) - [j6]Xuan Truong Nguyen
, Hyuk-Jae Lee
, Hyun Kim
:
A Low-Cost Hardware Design of a 1-D SPIHT Algorithm for Video Display Systems. IEEE Trans. Consumer Electron. 64(1): 44-52 (2018) - [j5]Hyun Kim
, Albert No
, Hyuk-Jae Lee
:
SPIHT Algorithm With Adaptive Selection of Compression Ratio Depending on DWT Coefficients. IEEE Trans. Multim. 20(12): 3200-3211 (2018) - [c8]Duy Thanh Nguyen, Hyun Kim, Hyuk-Jae Lee, Ik Joon Chang:
An Approximate Memory Architecture for a Reduction of Refresh Power Consumption in Deep Learning Applications. ISCAS 2018: 1-5 - 2017
- [j4]Hyun Kim, Hyuk-Jae Lee:
A low-power surveillance video coding system with early background subtraction and adaptive frame memory compression. IEEE Trans. Consumer Electron. 63(4): 359-367 (2017) - [c7]Dinh Van Luan, Nguyen Xuan Truong, Hyun Kim, Hyuk-Jae Lee:
Implementation of the XY2-100 protocol on low-cost microcontroller. ISOCC 2017: 86-87 - 2016
- [j3]Hyun Kim, Chae-Eun Rhee, Hyuk-Jae Lee:
A Low-Power Video Recording System With Multiple Operation Modes for H.264 and Light-Weight Compression. IEEE Trans. Multim. 18(4): 603-613 (2016) - [c6]Hyun Kim, Ik Joon Chang, Hyuk-Jae Lee:
An adaptive selection of an SRAM cell size for power reduction in an H.264/AVC encoder. ICCE 2016: 528-529 - 2015
- [j2]Sunwoong Kim
, Donghyeon Lee
, Hyun Kim, Nguyen Xuan Truong, Jin-Sung Kim:
An enhanced one-dimensional SPIHT algorithm and its implementation for TV systems. Displays 40: 68-77 (2015) - [j1]Hyun Kim, Chae-Eun Rhee, Hyuk-Jae Lee:
An Effective Combination of Power Scaling for H.264/AVC Compression. IEEE Trans. Very Large Scale Integr. Syst. 23(11): 2685-2689 (2015) - 2014
- [c5]Hyun Kim, Chae-Eun Rhee, Hyuk-Jae Lee:
A low-power hybrid video recording system with H.264/AVC and light-weight compression. ACSSC 2014: 2160-2162 - 2013
- [c4]Hyun Kim, Chae-Eun Rhee, Hyuk-Jae Lee:
Address generation for lossless frame memory compression in an H.264/AVC encoder. ICCE 2013: 570-571 - [c3]Hyun Kim, Chae-Eun Rhee, Hyuk-Jae Lee:
A low-power video recording system with H.264/AVC and light-weight compression. SiPS 2013: 183-188 - 2012
- [c2]Chae-Eun Rhee, Hyun Kim, Hyuk-Jae Lee:
An inter-frame macroblock schedule for memory access reduction in H.264/AVC bi-directional prediction. ISOCC 2012: 33-36 - 2011
- [c1]Hyun Kim, Chae-Eun Rhee, Jin-Sung Kim, Sunwoong Kim
, Hyuk-Jae Lee:
Power-aware design with various low-power algorithms for an H.264/AVC encoder. ISCAS 2011: 571-574
Coauthor Index
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