Power-aware design with various low-power algorithms for an H.264/AVC encoder. - Hyun Kim 001; Chae-Eun Rhee; Jin-Sung Kim; Sunwoong Kim; Hyuk-Jae Lee (ISCAS, 2011)

An inter-frame macroblock schedule for memory access reduction in H.264/AVC bi-directional prediction. - Chae-Eun Rhee; Hyun Kim 001; Hyuk-Jae Lee (ISOCC, 2012)

Address generation for lossless frame memory compression in an H.264/AVC encoder. - Hyun Kim 001; Chae-Eun Rhee; Hyuk-Jae Lee (ICCE, 2013)

A low-power video recording system with H.264/AVC and light-weight compression. - Hyun Kim 001; Chae-Eun Rhee; Hyuk-Jae Lee (SiPS, 2013)

A low-power hybrid video recording system with H.264/AVC and light-weight compression. - Hyun Kim 001; Chae-Eun Rhee; Hyuk-Jae Lee (ACSSC, 2014)

An enhanced one-dimensional SPIHT algorithm and its implementation for TV systems. - Sunwoong Kim; Donghyeon Lee; Hyun Kim 001; Nguyen Xuan Truong; Jin-Sung Kim (Displays, 2015)

An Effective Combination of Power Scaling for H.264/AVC Compression. - Hyun Kim 001; Chae-Eun Rhee; Hyuk-Jae Lee (IEEE Trans. Very Large Scale Integr. Syst., 2015)

An adaptive selection of an SRAM cell size for power reduction in an H.264/AVC encoder. - Hyun Kim 001; Ik Joon Chang; Hyuk-Jae Lee (ICCE, 2016)

A Low-Power Video Recording System With Multiple Operation Modes for H.264 and Light-Weight Compression. - Hyun Kim 001; Chae-Eun Rhee; Hyuk-Jae Lee (IEEE Trans. Multim., 2016)

Nonlithographic fabrication of inflatable and deflatable polydimethylsiloxane (PDMS) micro-channels for magnetic actuation. - Hyun Kim 001; Pyojin Kim; Jong-Mo Seo (EMBC, 2017)

Simple and fast polydimethylsiloxane (PDMS) patterning using a cutting plotter and vinyl adhesives to achieve etching results. - Hyun Kim 001; Sun-Young Yoo; Ji Sung Kim; Zihuan Wang; Woon-Hee Lee; Kyo-In Koo; Jong-Mo Seo; Dong-Il Cho (EMBC, 2017)

Implementation of the XY2-100 protocol on low-cost microcontroller. - Dinh Van Luan; Nguyen Xuan Truong; Hyun Kim 001; Hyuk-Jae Lee (ISOCC, 2017)

A low-power surveillance video coding system with early background subtraction and adaptive frame memory compression. - Hyun Kim 001; Hyuk-Jae Lee (IEEE Trans. Consumer Electron., 2017)

An Approximate Memory Architecture for a Reduction of Refresh Power Consumption in Deep Learning Applications. - Duy Thanh Nguyen; Hyun Kim 001; Hyuk-Jae Lee; Ik Joon Chang (ISCAS, 2018)

Optimal Selection of SRAM Bit-Cell Size for Power Reduction in Video Compression. - Hyun Kim 001; Ik Joon Chang; Hyuk-Jae Lee (IEEE J. Emerg. Sel. Topics Circuits Syst., 2018)

A Low-Cost Hardware Design of a 1-D SPIHT Algorithm for Video Display Systems. - Xuan Truong Nguyen; Hyuk-Jae Lee; Hyun Kim 001 (IEEE Trans. Consumer Electron., 2018)

SPIHT Algorithm With Adaptive Selection of Compression Ratio Depending on DWT Coefficients. - Hyun Kim 001; Albert No; Hyuk-Jae Lee (IEEE Trans. Multim., 2018)

A Hardware-Friendly Compression Algorithm for Profiling DDR4 Memory Accesses. - Xuan Truong Nguyen; Jiwoong Choi; Hyuk-Jae Lee; Hyun Kim 001 (ICEIC, 2019)

Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving. - Jiwoong Choi; Dayoung Chun; Hyun Kim 001; Hyuk-Jae Lee (ICCV, 2019)

ROI-Based LiDAR Sampling Algorithm in on-Road Environment for Autonomous Driving. - Xuan Truong Nguyen; Khac-Thai Nguyen; Hyuk-Jae Lee; Hyun Kim 001 (IEEE Access, 2019)

An Effective DRAM Address Remapping for Mitigating Rowhammer Errors. - Moonsoo Kim; Jungwoo Choi; Hyun Kim 001; Hyuk-Jae Lee (IEEE Trans. Computers, 2019)

Integration and Boost of a Read-Modify-Write Module in Phase Change Memory System. - Hyokeun Lee; Moonsoo Kim; Hyunchul Kim; Hyun Kim 001; Hyuk-Jae Lee (IEEE Trans. Computers, 2019)

A High-Throughput Hardware Accelerator for Lossless Compression of a DDR4 Command Trace. - Jiwoong Choi; Boyeal Kim; Hyun Kim 001; Hyuk-Jae Lee (IEEE Trans. Very Large Scale Integr. Syst., 2019)

A High-Throughput and Power-Efficient FPGA Implementation of YOLO CNN for Object Detection. - Duy Thanh Nguyen; Tuan Nghia Nguyen 002; Hyun Kim 001; Hyuk-Jae Lee (IEEE Trans. Very Large Scale Integr. Syst., 2019)

Uncertainty-based Object Detector for Autonomous Driving Embedded Platforms. - Jiwoong Choi; Dayoung Chun; Hyuk-Jae Lee; Hyun Kim 001 (AICAS, 2020)

PCM: Precision-Controlled Memory System for Energy Efficient Deep Neural Network Training. - Boyeal Kim; Sang Hyun Lee; Hyun Kim 001; Duy Thanh Nguyen; Minh-Son Le; Ik Joon Chang; Dohun Kwon; Jin Hyeok Yoo; Jun Won Choi; Hyuk-Jae Lee (DATE, 2020)

Mixture of Deterministic and Stochastic Quantization Schemes for Lightweight CNN. - Sungrae Kim; Hyun Kim 001 (ISOCC, 2020)

Mask-Soft Filter Pruning for Lightweight CNN Inference. - Nam Joon Kim; Hyun Kim 001 (ISOCC, 2020)

Instant and Accurate Instance Segmentation Equipped with Path Aggregation and Attention Gate. - Seung Il Lee; Hyun Kim 001 (ISOCC, 2020)

An MAE-aware ROI Sampling Model for LiDAR. - Quan-Dung Pham; Xuan Truong Nguyen; Hyuk-Jae Lee; Hyun Kim 001 (ISOCC, 2020)

Mitigating Write Disturbance Errors of Phase-Change Memory as In-Module Approach. - Hyokeun Lee; Seungyong Lee 003; Byeongki Song; Moonsoo Kim; Seokbo Shim; Hyun Kim 001; Hyuk-Jae Lee (CoRR, 2020)

An Approximate Memory Architecture for Energy Saving in Deep Learning Applications. - Duy Thanh Nguyen; Huy Hung Nguyen; Hyun Kim 001; Hyuk-Jae Lee (IEEE Trans. Circuits Syst. I Fundam. Theory Appl., 2020)

An Efficient Sampling Algorithm With a K-NN Expanding Operator for Depth Data Acquisition in a LiDAR System. - Xuan Truong Nguyen; Hyun Kim 001; Hyuk-Jae Lee (IEEE Trans. Circuits Syst. Video Technol., 2020)

A Low-Cost and High-Throughput FPGA Implementation of the Retinex Algorithm for Real-Time Video Enhancement. - Jin Woo Park; Hyokeun Lee; Boyeal Kim; Dong-Goo Kang; Seung Oh Jin; Hyun Kim 001; Hyuk-Jae Lee (IEEE Trans. Very Large Scale Integr. Syst., 2020)

DC-AC: Deep Correlation-Based Adaptive Compression of Feature Map Planes in Convolutional Neural Networks. - Seung-Hwan Bae; Hyuk-Jae Lee; Hyun Kim 001 (ISCAS, 2021)

Cache Compression with Golomb-Rice Code and Quantization for Convolutional Neural Networks. - Seung-Hwan Bae; Hyuk-Jae Lee; Hyun Kim 001 (ISCAS, 2021)

Hardware-friendly Log-scale Quantization for CNNs with Activation Functions Containing Negative Values. - Dahun Choi; Hyun Kim 001 (ISOCC, 2021)

Implementation of Optimal CNN Accelerators for Mobile Devices: Algorithm, Architecture, and Memory System Co-Design. - Hyun Kim 001 (ISOCC, 2021)

Continual Learning for Instance Segmentation to Mitigate Catastrophic Forgetting. - Jeong Jun Lee; Seung Il Lee; Hyun Kim 001 (ISOCC, 2021)

Zero-Centered Fixed-Point Quantization With Iterative Retraining for Deep Convolutional Neural Network-Based Object Detectors. - Sungrae Kim; Hyun Kim 001 (IEEE Access, 2021)

CNN-Based Mask-Pose Fusion for Detecting Specific Persons on Heterogeneous Embedded Systems. - Jeongjun Lee; Jihoon Jang 001; Jinhong Lee; Dayoung Chun; Hyun Kim 001 (IEEE Access, 2021)

RL-SPIHT: Reinforcement Learning-Based Adaptive Selection of Compression Ratios for 1-D SPIHT Algorithm. - Jin Shin; Hyun Kim 001 (IEEE Access, 2021)

Layer-Specific Optimization for Mixed Data Flow With Mixed Precision in FPGA Design for CNN-Based Object Detectors. - Duy Thanh Nguyen; Hyun Kim 001; Hyuk-Jae Lee (IEEE Trans. Circuits Syst. Video Technol., 2021)

Hardware-Friendly Logarithmic Quantization with Mixed-Precision for MobileNetV2. - Dahun Choi; Hyun Kim 001 (AICAS, 2022)

Power-Efficient Double-Cyclic Low-Precision Training for Convolutional Neural Networks. - Sungrae Kim; Hyun Kim 001 (AICAS, 2022)

DC-MPQ: Distributional Clipping-based Mixed-Precision Quantization for Convolutional Neural Networks. - Seungjin Lee; Hyun Kim 001 (AICAS, 2022)

Activation Distribution-based Layer-wise Quantization for Convolutional Neural Networks. - Subin Ki; Hyun Kim 001 (ICEIC, 2022)

Fine-tuned SPIHT Algorithm to Improve Compression Efficiency. - Jin Shin; Hyun Kim 001 (ICEIC, 2022)

GaussianMask: Uncertainty-aware Instance Segmentation based on Gaussian Modeling. - Seung Il Lee; Hyun Kim 001 (ICPR, 2022)

Feature Distribution-based Knowledge Distillation for Deep Neural Networks. - Hyeonseok Hong; Hyun Kim 001 (ISOCC, 2022)

Performance Analysis of a Phase-Change Memory System on Various CNN Inference Workloads. - Jihoon Jang 001; Hyun Kim 001; Hyokeun Lee (ISOCC, 2022)

PCMCsim: An Accurate Phase-Change Memory Controller Simulator and its Performance Analysis. - Hyokeun Lee; Hyungsuk Kim; Seokbo Shim; Seungyong Lee 003; Do-sun Hong; Hyuk-Jae Lee; Hyun Kim 001 (ISPASS, 2022)

WL-WD: Wear-Leveling Solution to Mitigate Write Disturbance Errors for Phase-Change Memory. - Moonsoo Kim; Hyokeun Lee; Hyun Kim 001; Hyuk-Jae Lee (IEEE Access, 2022)

Review of Optimal Convolutional Neural Network Accelerator Platforms for Mobile Devices. - Hyun Kim 001 (J. Comput. Sci. Eng., 2022)

PPT-KP: Pruning Point Training-based Kernel Pruning for Deep Convolutional Neural Networks. - Kwanghyun Koo; Hyun Kim 001 (AICAS, 2023)

GPIL: Gradient with PseudoInverse Learning for High Accuracy Fine-Tuning. - Gilha Lee; Nam Joon Kim; Hyun Kim 001 (AICAS, 2023)

FieldHAR: A Fully Integrated End-to-End RTL Framework for Human Activity Recognition with Neural Networks from Heterogeneous Sensors. - Mengxi Liu; Bo Zhou 005; Zimin Zhao; Hyeonseok Hong; Hyun Kim 001; Sungho Suh; Vítor Fortes Rey; Paul Lukowicz (ASAP, 2023)

Characterizing Memory Access Patterns of Various Convolutional Neural Networks for Utilizing Processing-in-Memory. - Jihoon Jang 001; Hyun Kim 001; Hyokeun Lee (ICEIC, 2023)

AGT: Channel Pruning Using Adaptive Gradient Training for Accelerating Convolutional Neural Networks. - Nam Joon Kim; Hyun Kim 001 (ICEIC, 2023)

UCR-SSL: Uncertainty-Based Consistency Regularization for Semi-Supervised Learning. - Seungil Lee; Hyun Kim 001; Dayoung Chun (ICEIC, 2023)

DWT+DWT: Deep Learning Domain Generalization Techniques Using Discrete Wavelet Transform with Deep Whitening Transform. - Jin Shin; Hyun Kim 001 (ICEIC, 2023)

RepSGD: Channel Pruning Using Reparamerization for Accelerating Convolutional Neural Networks. - Nam Joon Kim; Hyun Kim 001 (ISCAS, 2023)

A Spatio-Temporal Switchable Data Prefetcher for Convolutional Neural Networks. - Jihoon Jang 001; Hyun Kim 001; Hyokeun Lee (ISOCC, 2023)

Hardware-friendly Activation Functions for HybridViT Models. - Beom Jin Kang; Nam Joon Kim; Jong Ho Lee; Hyun Kim 001 (ISOCC, 2023)

CP-CNN: Computational Parallelization of CNN-Based Object Detectors in Heterogeneous Embedded Systems for Autonomous Driving. - Dayoung Chun; Jiwoong Choi; Hyuk-Jae Lee; Hyun Kim 001 (IEEE Access, 2023)

V-SKP: Vectorized Kernel-Based Structured Kernel Pruning for Accelerating Deep Convolutional Neural Networks. - Kwanghyun Koo; Hyun Kim 001 (IEEE Access, 2023)

Multi-Step Training Framework Using Sparsity Training for Efficient Utilization of Accumulated New Data in Convolutional Neural Networks. - Jeongjun Lee; Hyun Kim 001 (IEEE Access, 2023)

FP-AGL: Filter Pruning With Adaptive Gradient Learning for Accelerating Deep Convolutional Neural Networks. - Nam Joon Kim; Hyun Kim 001 (IEEE Trans. Multim., 2023)

An In-Module Disturbance Barrier for Mitigating Write Disturbance in Phase-Change Memory. - Hyokeun Lee; Seungyong Lee 003; Byeongki Song; Moonsoo Kim; Seokbo Shim; Hyuk-Jae Lee; Hyun Kim 001 (IEEE Trans. Computers, 2023)

Dedicated FPGA Implementation of the Gaussian TinyYOLOv3 Accelerator. - Subin Ki; Juntae Park; Hyun Kim 001 (IEEE Trans. Circuits Syst. II Express Briefs, 2023)

Sensor Data Augmentation from Skeleton Pose Sequences for Improving Human Activity Recognition. - Parham Zolfaghari; Vítor Fortes Rey; Lala Shakti Swarup Ray; Hyun Kim 001; Sungho Suh; Paul Lukowicz (ABC, 2024)

PF-Training: Parameter Freezing for Efficient On-Device Training of CNN-based Object Detectors in Low-Resource Environments. - Dayoung Chun; Hyuk-Jae Lee; Hyun Kim 001 (AICAS, 2024)

SRU-Q: Hardware-friendly Stochastic Rounding Unit-based Gradient Quantization for CNN Training. - Sangbeom Jeong; Dahun Choi; Hyun Kim 001 (AICAS, 2024)

ACC: Adaptive Compression Framework for Efficient On-device CNN Training. - Gilha Lee; Seungil Lee; Hyun Kim 001 (AICAS, 2024)

GDS: Gradient Distribution Scaling-based Gradient Quantization for Low-complexity and Hardware-friendly Training of Instance Segmentation Models. - Dahun Choi; Hyun Kim 001 (ICEIC, 2024)

Implementation of Tiled Point-Wise Convolution in MobileNet for Parallel Processing. - Hyeon Seok Hong; Hyun Kim 001 (ICEIC, 2024)

An Architecture-Level Framework for Enabling Processing-Using-Memory Simulations in Deep Neural Networks. - Inseong Hwang; Jihoon Jang 001; Hyun Kim 001 (ICEIC, 2024)

Mixed Precision Quantization with Hardware-Friendly Activation Functions for Hybrid ViT Models. - Beom Jin Kang; Dahun Choi; Hyun Kim 001 (ICEIC, 2024)

Extreme Pruning Technique Based on Filter Deactivation Using Sparsity Training for Deep Convolutional Neural Networks. - Kwanghyun Koo; Hyun Kim 001 (ICEIC, 2024)

Enhancing Pseudo-Labeling Performance in Object Detection Using Gaussian Mixture Modeled Uncertainty. - Seungil Lee; Hyun Kim 001 (ICEIC, 2024)

A Simplified Feature Alignment Strategy for Image Classification Across Domains. - Jin Shin; Hyun Kim 001 (ICEIC, 2024)

HyQ: Hardware-Friendly Post-Training Quantization for CNN-Transformer Hybrid Networks. - Nam Joon Kim; Jongho Lee; Hyun Kim 001 (IJCAI, 2024)

ARC: Adaptive Rounding and Clipping Considering Gradient Distribution for Deep Convolutional Neural Network Training. - Dahun Choi; Hyun Kim 001 (ISCAS, 2024)

EDeN: Enabling Low-Power CNN Inference on Edge Devices Using Prefetcher-assisted NVM Systems. - Jihoon Jang 001; Hyokeun Lee; Hyun Kim 001 (ISLPED, 2024)

Hardware-aware Network Compression for Hybrid Vision Transformer via Low-Rank Approximation. - Beom Jin Kang; Nam Joon Kim; Hyun Kim 001 (ISOCC, 2024)

FB-SKP: Front-Back Structured Kernel Pruning via Group Convolution without Increasing Memory. - Kwanghyun Koo; Hyun Kim 001 (ISOCC, 2024)

HLQ: Hardware-Friendly Logarithmic Quantization Aware Training for Power-Efficient Low-Precision CNN Models. - Dahun Choi; Juntae Park; Hyun Kim 001 (IEEE Access, 2024)

DCT-ViT: High-Frequency Pruned Vision Transformer With Discrete Cosine Transform. - Jongho Lee; Hyun Kim 001 (IEEE Access, 2024)

A survey of FPGA and ASIC designs for transformer inference acceleration and optimization. - Beom Jin Kang; Haein Lee; Seok Kyu Yoon; Young Chan Kim; Sangbeom Jeong; Seong Jun O; Hyun Kim 001 (J. Syst. Archit., 2024)

USD: Uncertainty-Based One-Phase Learning to Enhance Pseudo-Label Reliability for Semi-Supervised Object Detection. - Dayoung Chun; Seungil Lee; Hyun Kim 001 (IEEE Trans. Multim., 2024)

Trunk Pruning: Highly Compatible Channel Pruning for Convolutional Neural Networks Without Fine-Tuning. - Nam Joon Kim; Hyun Kim 001 (IEEE Trans. Multim., 2024)

Vision transformer models for mobile/edge devices: a survey. - Seung Il Lee; Kwanghyun Koo; Jong Ho Lee; Gilha Lee; Sangbeom Jeong; Seongjun O; Hyun Kim 001 (Multim. Syst., 2024)

Survey of convolutional neural network accelerators on field-programmable gate array platforms: architectures and optimization techniques. - Hyeonseok Hong; Dahun Choi; Namjoon Kim; Haein Lee; Beom Jin Kang; Huibeom Kang; Hyun Kim 001 (J. Real Time Image Process., 2024)

Mobile-X: Dedicated FPGA Implementation of the MobileNet Accelerator Optimizing Depthwise Separable Convolution. - Hyeonseok Hong; Dahun Choi; Namjoon Kim; Hyun Kim 001 (IEEE Trans. Circuits Syst. II Express Briefs, 2024)

GradQ-ViT: Robust and Efficient Gradient Quantization for Vision Transformers. - Dahun Choi; Hyun Kim 001 (AAAI, 2025)

LowGradQ: Adaptive Gradient Quantization for Low-Bit CNN Training via Kernel Density Estimation-Guided Thresholding and Hardware-Efficient Stochastic Rounding Unit. - Sangbeom Jeong; Seungil Lee; Hyun Kim 001 (DATE, 2025)

Optimizing Deep Neural Network Precision for Processing-in-Memory: A Memory Bottleneck Perspective. - Inseong Hwang; Jihoon Jang 001; Hyun Kim 001 (ICEIC, 2025)

Evaluation of 2T0C DRAM-Based Processing-in-Memory Systems for Accelerating Deep Neural Network Models. - Jihoon Jang 001; Inseong Hwang; Hyun Kim 001 (ICEIC, 2025)

GASQ: Hardware-Friendly Gradient Distribution-Aware Split Quantization for Low-Bit CNN Training. - Sangbeom Jeong; Kwanghyun Koo; Hyun Kim 001 (ICEIC, 2025)

LAMP-Q: Layer Sensitivity-Aware Mixed-Precision Quantization for MobileNetV3. - Seokkyu Yoon; Namjoon Kim; Hyun Kim 001 (ICEIC, 2025)

Hardware-Friendly Quantization via Outlier Scaling in Convolution-Attention-Based Hybrid Networks. - Nam Joon Kim; Hyun Kim 001 (ICCE, 2025)

Feature Alignment in Vision Mamba to Resolve Domain Shift of Mobile Medical Devices. - Jin Shin; Hyun Kim 001 (ICCE, 2025)

XNC: XOR and NOT-Based Lossless Compression for Optimizing Unquantized Embedding Layers in Large Language Models. - Junghyeok Lee; Jihoon Jang 001; Hyun Kim 001 (ISCAS, 2025)

PIM-BEACON: A Benchmarking and Emulation Framework Supporting Adaptive CONfigurations in DRAM-Based Processing-in-Memory Systems. - Inseong Hwang; Jihoon Jang 001; Chaewon Park; Hyun Kim 001 (ISPASS, 2025)

VFT: A versatile fine-tuning scheme based on feature distribution-aware knowledge distillation for lightweight convolutional neural networks. - Hyeonseok Hong; Hyun Kim 001 (Eng. Appl. Artif. Intell., 2025)

VFF-Net: Evolving forward-forward algorithms into convolutional neural networks for enhanced computational insights. - Gilha Lee; Jin Shin; Hyun Kim 001 (Neural Networks, 2025)

Survey of CPU and memory simulators in computer architecture: A comprehensive analysis including compiler integration and emerging technology applications. - Inseong Hwang; Junghyeok Lee; Huibeom Kang; Gilhyeon Lee; Hyun Kim 001 (Simul. Model. Pract. Theory, 2025)

MCM-SR: Multiple Constant Multiplication-Based CNN Streaming Hardware Architecture for Super-Resolution. - Seung-Hwan Bae; Hyuk-Jae Lee; Hyun Kim 001 (IEEE Trans. Very Large Scale Integr. Syst., 2025)

Lightweight Deepfake Detection Based on Multi-Feature Fusion. - Siddiqui Muhammad Yasir; Hyun Kim 001 (CoRR, 2025)

NPC: A Non-Conflicting Processing-in-Memory Controller in DDR Memory Systems. - Seungyong Lee 003; Sanghyun Lee; Minseok Seo; Chunmyung Park; Woojae Shin; Hyuk-Jae Lee; Hyun Kim 001 (IEEE Trans. Computers, 2025)