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2020 – today
- 2024
[c10]Gwangtae Park, Seokchan Song, Haoyang Sang
, Dongseok Im, Donghyeon Han, Sangyeob Kim, Hongseok Lee, Hoi-Jun Yoo:
A Low-power and Real-time Neural-Rendering Dense SLAM Processor with 3-Level Hierarchical Sparsity Exploitation. COOL CHIPS 2024: 1-3- [c9]Seokchan Song, Haoyang Sang, Dongseok Im, Donghyeon Han, Sangyeob Kim, Hongseok Lee, Hoi-Jun Yoo:
Space-Mate: A 303.5mW Real-Time NeRF SLAM Processor with Sparse-Mixture-of-Experts-based Acceleration. HCS 2024: 1 - [c8]Jongjun Park, Seryeong Kim, Wonhoon Park, Seokchan Song, Hoi-Jun Yoo:
A 3.55 mJ/frame Energy-efficient Mixed-Transformer based Semantic Segmentation Accelerator for Mobile Devices. ISCAS 2024: 1-5 - [c7]Gwangtae Park, Seokchan Song, Haoyang Sang, Dongseok Im, Donghyeon Han, Sangyeob Kim, Hongseok Lee, Hoi-Jun Yoo:
20.8 Space-Mate: A 303.5mW Real-Time Sparse Mixture-of-Experts-Based NeRF-SLAM Processor for Mobile Spatial Computing. ISSCC 2024: 374-376 - [c6]Seryeong Kim, Seokchan Song, Wonhoon Park, Junha Ryu, Sangyeob Kim, Gwangtae Park, Soyeon Kim, Hoi-Jun Yoo:
NeRF-Navi: A 93.6-202.9µJ/task Switchable Approximate-Accurate NeRF Path Planning Processor with Dual Attention Engine and Outlier Bit-Offloading Core. VLSI Technology and Circuits 2024: 1-2 - 2023
- [c5]Seokchan Song, Donghyeon Han, Sangjin Kim, Sangyeob Kim, Gwangtae Park, Hoi-Jun Yoo:
GPPU: A 330.4-μJ/ task Neural Path Planning Processor with Hybrid GNN Acceleration for Autonomous 3D Navigation. VLSI Technology and Circuits 2023: 1-2 - 2022
- [j3]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
A Mobile DNN Training Processor With Automatic Bit Precision Search and Fine-Grained Sparsity Exploitation. IEEE Micro 42(2): 16-25 (2022) - [j2]Seokchan Song, Soyeon Kim, Gwangtae Park, Donghyeon Han, Hoi-Jun Yoo:
A 49.5 mW Multi-Scale Linear Quantized Online Learning Processor for Real-Time Adaptive Object Detection. IEEE Trans. Circuits Syst. II Express Briefs 69(5): 2443-2447 (2022) - [c4]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
A 0.95 mJ/frame DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation. AICAS 2022: 37-40 - [c3]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
A DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation. AICAS 2022: 501 - [c2]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
HNPU-V2: A 46.6 FPS DNN Training Processor for Real-World Environmental Adaptation based Robust Object Detection on Mobile Devices. HCS 2022: 1-18 - 2021
- [j1]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
HNPU: An Adaptive DNN Training Processor Utilizing Stochastic Dynamic Fixed-Point and Active Bit-Precision Searching. IEEE J. Solid State Circuits 56(9): 2858-2869 (2021) - [c1]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
An Energy-Efficient Deep Neural Network Training Processor with Bit-Slice-Level Reconfigurability and Sparsity Exploitation. COOL CHIPS 2021: 1-3
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