Sangyun Oh

According to our database, Sangyun Oh authored at least 8 papers between 2017 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

MLogNet: A Logarithmic Quantization-Based Accelerator for Depthwise Separable Convolution.

Jooyeon Choi, Hyeonuk Sim, Sangyun Oh, Sugil Lee, Jongeun Lee

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

Non-uniform Step Size Quantization for Accurate Post-training Quantization.

Sangyun Oh, Hyeonuk Sim, Jounghyun Kim, Jongeun Lee

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Automated Log-Scale Quantization for Low-Cost Deep Neural Networks.

Sangyun Oh, Hyeonuk Sim, Sugil Lee, Jongeun Lee

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

RRNet: Repetition-Reduction Network for Energy Efficient Depth Estimation.

Sangyun Oh, Hye-Jin S. Kim, Jongeun Lee, Junmo Kim

IEEE Access, 2020

Analysis and Solution of CNN Accuracy Reduction over Channel Loop Tiling.

Yesung Kang, Yoonho Park, Sunghoon Kim, Eunji Kwon, Taeho Lim, Sangyun Oh, Mingyu Woo, Seokhyeong Kang

Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

2019

RRNet: Repetition-Reduction Network for Energy Efficient Decoder of Depth Estimation.

Sangyun Oh, Hye-Jin S. Kim, Jongeun Lee, Junmo Kim

CoRR, 2019

2017

Efficient Execution of Stream Graphs on Coarse-Grained Reconfigurable Architectures.

Sangyun Oh, Hongsik Lee, Jongeun Lee

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2017

Design space exploration of FPGA accelerators for convolutional neural networks.

Atul Rahman, Sangyun Oh, Jongeun Lee, Kiyoung Choi

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2017