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)

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)

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)

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)

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 49.5 mW Multi-Scale Linear Quantized Online Learning Processor for Real-Time Adaptive Object Detection. - Seokchan Song; Soyeon Kim; Gwangtae Park; Donghyeon Han; Hoi-Jun Yoo (IEEE Trans. Circuits Syst. II Express Briefs, 2022)

GPPU: A 330.4-μJ/ task Neural Path Planning Processor with Hybrid GNN Acceleration for Autonomous 3D Navigation. - Seokchan Song; Donghyeon Han; Sangjin Kim; Sangyeob Kim; Gwangtae Park; Hoi-Jun Yoo (VLSI Technology and 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)

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)

A 3.55 mJ/frame Energy-efficient Mixed-Transformer based Semantic Segmentation Accelerator for Mobile Devices. - Jongjun Park; Seryeong Kim; Wonhoon Park; Seokchan Song; Hoi-Jun Yoo (ISCAS, 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)

NeRF-Navi: A 93.6-202.9µJ/task Switchable Approximate-Accurate NeRF Path Planning Processor with Dual Attention Engine and Outlier Bit-Offloading Core. - Seryeong Kim; Seokchan Song; Wonhoon Park; Junha Ryu; Sangyeob Kim; Gwangtae Park; Soyeon Kim; Hoi-Jun Yoo (VLSI Technology and Circuits, 2024)

An Energy-Efficient CNN/Transformer Hybrid Neural Semantic Segmentation Processor With Chunk-Based Bit Plane Data Compression and Similarity-Based Token-Level Skipping Exploitation. - Jongjun Park; Seryeong Kim; Wonhoon Park; Seokchan Song; Hoi-Jun Yoo (IEEE Trans. Circuits Syst. I Regul. Pap., 2024)

IRIS: A 8.55mJ/frame Spatial Computing SoC for Interactable Rendering and Surface-Aware Modeling with 3D Gaussian Splatting. - Seokchan Song; Seryeong Kim; Wonhoon Park; Jongjun Park; Sanghyuk An; Gwangtae Park; Minseo Kim; Hoi-Jun Yoo (ISSCC, 2025)