DT-CNN: Dilated and Transposed Convolution Neural Network Accelerator for Real-Time Image Segmentation on Mobile Devices. - Dongseok Im; Donghyeon Han; Sungpill Choi; Sanghoon Kang; Hoi-Jun Yoo (ISCAS, 2019)

7.4 GANPU: A 135TFLOPS/W Multi-DNN Training Processor for GANs with Speculative Dual-Sparsity Exploitation. - Sanghoon Kang; Donghyeon Han; Juhyoung Lee; Dongseok Im; Sangyeob Kim; Soyeon Kim; Hoi-Jun Yoo (ISSCC, 2020)

A 4.45 ms Low-Latency 3D Point-Cloud-Based Neural Network Processor for Hand Pose Estimation in Immersive Wearable Devices. - Dongseok Im; Sanghoon Kang; Donghyeon Han; Sungpill Choi; Hoi-Jun Yoo (VLSI Circuits, 2020)

DT-CNN: An Energy-Efficient Dilated and Transposed Convolutional Neural Network Processor for Region of Interest Based Image Segmentation. - Dongseok Im; Donghyeon Han; Sungpill Choi; Sanghoon Kang; Hoi-Jun Yoo (IEEE Trans. Circuits Syst., 2020)

A 1.15 TOPS/W Energy-Efficient Capsule Network Accelerator for Real-Time 3D Point Cloud Segmentation in Mobile Environment. - Gwangtae Park; Dongseok Im; Donghyeon Han; Hoi-Jun Yoo (IEEE Trans. Circuits Syst. II Express Briefs, 2020)

An Energy-Efficient Deep Neural Network Training Processor with Bit-Slice-Level Reconfigurability and Sparsity Exploitation. - Donghyeon Han; Dongseok Im; Gwangtae Park; Youngwoo Kim; Seokchan Song; Juhyoung Lee; Hoi-Jun Yoo (COOL CHIPS, 2021)

PNNPU: A Fast and Efficient 3D Point Cloud-based Neural Network Processor with Block-based Point Processing for Regular DRAM Access. - Sangjin Kim; Juhyoung Lee; Dongseok Im; Hoi-Jun Yoo (HCS, 2021)

A 3.6 TOPS/W Hybrid FP-FXP Deep Learning Processor with Outlier Compensation for Image-to-Image Application. - Zhiyong Li 016; Dongseok Im; Jinsu Lee; Hoi-Jun Yoo (ISCAS, 2021)

PNNPU: A 11.9 TOPS/W High-speed 3D Point Cloud-based Neural Network Processor with Block-based Point Processing for Regular DRAM Access. - Sangjin Kim; Juhyoung Lee; Dongseok Im; Hoi-Jun Yoo (VLSI Circuits, 2021)

HNPU: An Adaptive DNN Training Processor Utilizing Stochastic Dynamic Fixed-Point and Active Bit-Precision Searching. - Donghyeon Han; Dongseok Im; Gwangtae Park; Youngwoo Kim; Seokchan Song; Juhyoung Lee; Hoi-Jun Yoo (IEEE J. Solid State Circuits, 2021)

GANPU: An Energy-Efficient Multi-DNN Training Processor for GANs With Speculative Dual-Sparsity Exploitation. - Sanghoon Kang; Donghyeon Han; Juhyoung Lee; Dongseok Im; Sangyeob Kim; Soyeon Kim; Junha Ryu; Hoi-Jun Yoo (IEEE J. Solid State Circuits, 2021)

A 0.82 μW CIS-Based Action Recognition SoC With Self-Adjustable Frame Resolution for Always-on IoT Devices. - Junha Ryu; Gwangtae Park; Dongseok Im; Ji-Hoon Kim 004; Hoi-Jun Yoo (IEEE Trans. Circuits Syst. II Express Briefs, 2021)

A 0.95 mJ/frame DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation. - Donghyeon Han; Dongseok Im; Gwangtae Park; Youngwoo Kim; Seokchan Song; Juhyoung Lee; Hoi-Jun Yoo (AICAS, 2022)

A DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation. - Donghyeon Han; Dongseok Im; Gwangtae Park; Youngwoo Kim; Seokchan Song; Juhyoung Lee; Hoi-Jun Yoo (AICAS, 2022)

An 0.92 mJ/frame High-quality FHD Super-resolution Mobile Accelerator SoC with Hybrid-precision and Energy-efficient Cache. - Zhiyong Li 016; Sangjin Kim; Dongseok Im; Donghyeon Han; Hoi-Jun Yoo (CICC, 2022)

A Low-power and Real-time 3D Object Recognition Processor with Dense RGB-D Data Acquisition in Mobile Platforms. - Dongseok Im; Gwangtae Park; Junha Ryu; Zhiyong Li 016; Sanghoon Kang; Donghyeon Han; Jinsu Lee; Wonhoon Park; Hankyul Kwon; Hoi-Jun Yoo (COOL CHIPS, 2022)

HNPU-V2: A 46.6 FPS DNN Training Processor for Real-World Environmental Adaptation based Robust Object Detection on Mobile Devices. - Donghyeon Han; Dongseok Im; Gwangtae Park; Youngwoo Kim; Seokchan Song; Juhyoung Lee; Hoi-Jun Yoo (HCS, 2022)

DSPU: A 281.6mW Real-Time Deep Learning-Based Dense RGB-D Data Acquisition with Sensor Fusion and 3D Perception System-on-Chip. - Dongseok Im; Gwangtae Park; Zhiyong Li 016; Junha Ryu; Sanghoon Kang; Donghyeon Han; Jinsu Lee; Wonhoon Park; Hankyul Kwon; Hoi-Jun Yoo (HCS, 2022)

An Efficient High-quality FHD Super-resolution Mobile Accelerator SoC with Hybrid-precision and Energy-efficient Cache. - Zhiyong Li 016; Sangjin Kim; Dongseok Im; Donghyeon Han; Hoi-Jun Yoo (HCS, 2022)

DSPU: A 281.6mW Real-Time Depth Signal Processing Unit for Deep Learning-Based Dense RGB-D Data Acquisition with Depth Fusion and 3D Bounding Box Extraction in Mobile Platforms. - Dongseok Im; Gwangtae Park; Zhiyong Li 016; Junha Ryu; Sanghoon Kang; Donghyeon Han; Jinsu Lee; Hoi-Jun Yoo (ISSCC, 2022)

Energy-efficient Dense DNN Acceleration with Signed Bit-slice Architecture. - Dongseok Im; Gwangtae Park; Zhiyong Li 016; Junha Ryu; Hoi-Jun Yoo (CoRR, 2022)

A Pipelined Point Cloud Based Neural Network Processor for 3-D Vision With Large-Scale Max Pooling Layer Prediction. - Dongseok Im; Donghyeon Han; Sanghoon Kang; Hoi-Jun Yoo (IEEE J. Solid State Circuits, 2022)

A Mobile DNN Training Processor With Automatic Bit Precision Search and Fine-Grained Sparsity Exploitation. - Donghyeon Han; Dongseok Im; Gwangtae Park; Youngwoo Kim; Seokchan Song; Juhyoung Lee; Hoi-Jun Yoo (IEEE Micro, 2022)

A 33.6 FPS Embedding based Real-time Neural Rendering Accelerator with Switchable Computation Skipping Architecture on Edge Device. - Jongjun Park; Donghyeon Han; Junha Ryu; Dongseok Im; Gwangtae Park; Hoi-Jun Yoo (A-SSCC, 2023)

Sibia: Signed Bit-slice Architecture for Dense DNN Acceleration with Slice-level Sparsity Exploitation. - Dongseok Im; Gwangtae Park; Zhiyong Li 016; Junha Ryu; Hoi-Jun Yoo (HPCA, 2023)

A 709.3 TOPS/W Event-Driven Smart Vision SoC with High-Linearity and Reconfigurable MRAM PIM. - Wenao Xie; Haoyang Sang; Beomseok Kwon; Dongseok Im; Sangjin Kim; Sangyeob Kim; Hoi-Jun Yoo (VLSI Technology and Circuits, 2023)

DSPU: An Efficient Deep Learning-Based Dense RGB-D Data Acquisition With Sensor Fusion and 3-D Perception SoC. - Dongseok Im; Gwangtae Park; Junha Ryu; Zhiyong Li 016; Sanghoon Kang; Donghyeon Han; Jinsu Lee; Wonhoon Park; Hankyul Kwon; Hoi-Jun Yoo (IEEE J. Solid State Circuits, 2023)

A Mobile 3-D Object Recognition Processor With Deep-Learning-Based Monocular Depth Estimation. - Dongseok Im; Gwangtae Park; Zhiyong Li 016; Junha Ryu; Sanghoon Kang; Donghyeon Han; Jinsu Lee; Wonhoon Park; Hankyul Kwon; Hoi-Jun Yoo (IEEE Micro, 2023)

An Efficient Deep-Learning-Based Super-Resolution Accelerating SoC With Heterogeneous Accelerating and Hierarchical Cache. - Zhiyong Li 016; Sangjin Kim; Dongseok Im; Donghyeon Han; Hoi-Jun Yoo (IEEE J. Solid State Circuits, 2023)

A Low-power and Real-time Neural-Rendering Dense SLAM Processor with 3-Level Hierarchical Sparsity Exploitation. - Gwangtae Park; Seokchan Song; Haoyang Sang; Dongseok Im; Donghyeon Han; Sangyeob Kim; Hongseok Lee; Hoi-Jun Yoo (COOL CHIPS, 2024)

A Low-Power Neural Graphics System for Instant 3D Modeling and Real-Time Rendering on Mobile AR/VR Devices. - Junha Ryu; Hankyul Kwon; Wonhoon Park; Zhiyong Li 016; Beomseok Kwon; Donghyeon Han; Dongseok Im; Sangyeob Kim; Hyungnam Joo; Minsung Kim; Hoi-Jun Yoo (COOL CHIPS, 2024)

NeuGPU: A Neural Graphics Processing Unit for Instant Modeling and Real-Time Rendering on Mobile AR/VR Devices. - Junha Ryu; Hankyul Kwon; Wonhoon Park; Zhiyong Li 016; Beomseok Kwon; Donghyeon Han; Dongseok Im; Sangyeob Kim; Hyungnam Joo; Minsung Kim; Hoi-Jun Yoo (HCS, 2024)

Space-Mate: A 303.5mW Real-Time NeRF SLAM Processor with Sparse-Mixture-of-Experts-based Acceleration. - Seokchan Song; Haoyang Sang; Dongseok Im; Donghyeon Han; Sangyeob Kim; Hongseok Lee; Hoi-Jun Yoo (HCS, 2024)

LUTein: Dense-Sparse Bit-Slice Architecture With Radix-4 LUT-Based Slice-Tensor Processing Units. - Dongseok Im; Hoi-Jun Yoo (HPCA, 2024)

20.8 Space-Mate: A 303.5mW Real-Time Sparse Mixture-of-Experts-Based NeRF-SLAM Processor for Mobile Spatial Computing. - Gwangtae Park; Seokchan Song; Haoyang Sang; Dongseok Im; Donghyeon Han; Sangyeob Kim; Hongseok Lee; Hoi-Jun Yoo (ISSCC, 2024)

20.7 NeuGPU: A 18.5mJ/Iter Neural-Graphics Processing Unit for Instant-Modeling and Real-Time Rendering with Segmented-Hashing Architecture. - Junha Ryu; Hankyul Kwon; Wonhoon Park; Zhiyong Li 016; Beomseok Kwon; Donghyeon Han; Dongseok Im; Sangyeob Kim; Hyungnam Joo; Hoi-Jun Yoo (ISSCC, 2024)

CamPU: A Multi-Camera Processing Unit for Deep Learning-based 3D Spatial Computing Systems. - Dongseok Im; Hoi-Jun Yoo (MICRO, 2024)

23.7 BROCA: A 52.4-to-559.2mW Mobile Social Agent System-on-Chip with Adaptive Bit-Truncate Unit and Acoustic-Cluster Bit Grouping. - Wooyoung Jo; Seongyon Hong; Jiwon Choi; Beomseok Kwon; Haoyang Sang; Dongseok Im; Sangyeob Kim; Sangjin Kim; Taekwon Lee; Hoi-Jun Yoo (ISSCC, 2025)

23.3 EdgeDiff: 418.4mJ/Inference Multi-Modal Few-Step Diffusion Model Accelerator with Mixed-Precision and Reordered Group Quantization. - Sangjin Kim; Jungjun Oh; Jeonggyu So; Yuseon Choi; Sangyeob Kim; Dongseok Im; Gwangtae Park; Hoi-Jun Yoo (ISSCC, 2025)

NeuGPU: An Energy-Efficient Neural Graphics Processing Unit for Instant Modeling and Real-Time Rendering on Mobile Devices. - Junha Ryu; Hankyul Kwon; Wonhoon Park; Zhiyong Li 016; Beomseok Kwon; Donghyeon Han; Dongseok Im; Sangyeob Kim; Hyungnam Joo; Minsung Kim; Hoi-Jun Yoo (IEEE J. Solid State Circuits, 2025)

ED-MPIM: An Energy-Efficient Event-Driven Smart Vision SoC With High-Linearity and Reconfigurable MRAM PIM. - Wenao Xie; Haoyang Sang; Beomseok Kwon; Dongseok Im; Sangjin Kim; Sangyeob Kim; Kangho Lee; Hoi-Jun Yoo (IEEE J. Solid State Circuits, 2025)