Joonsang Yu

According to our database, Joonsang Yu authored at least 24 papers between 2016 and 2026.

Collaborative distances:

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

2026

DANCE++: Differentiable Accelerator/Network Co-Exploration With Hard Constraints and Data-Free Training for Real-World Scenarios.

Kanghyun Choi, Deokki Hong, Hyeyoon Lee, Joonsang Yu, Noseong Park, Youngsok Kim, Jinho Lee

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., February, 2026

2025

ZIM: Zero-Shot Image Matting for Anything.

Beomyoung Kim, Chanyong Shin, Joonhyun Jeong, Hyungsik Jung, Se-Yun Lee, Sewhan Chun, Dong-Hyun Hwang, Joonsang Yu

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

2024

Towards Label-Efficient Human Matting: A Simple Baseline for Weakly Semi-Supervised Trimap-Free Human Matting.

Beomyoung Kim, Myeong-Yeon Yi, Joonsang Yu, Young Joon Yoo, Sung Ju Hwang

CoRR, 2024

EResFD: Rediscovery of the Effectiveness of Standard Convolution for Lightweight Face Detection.

Joonhyun Jeong, Beomyoung Kim, Joonsang Yu, Youngjoon Yoo

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

400G cost-effective EML for B5G/6G Fronthaul Network.

Seungchul Lee, Namje Kim, Miran Park, Kihong Yoon, Mihee Hwang, Joonsang Yu, Sangho Lee, O-Kyun Kwon

Proceedings of the Optical Fiber Communications Conference and Exhibition, 2024

Cost-effective IA-EML for 5G-advanced and 6G Fronthaul Networks.

Seungchul Lee, Namje Kim, Yonghan Kim, Miran Park, Jun-Hwan Shin, O-Kyun Kwon, Kihong Yoon, Mihee Hwang, Joonsang Yu

Proceedings of the 15th International Conference on Information and Communication Technology Convergence, 2024

ECLIPSE: Efficient Continual Learning in Panoptic Segmentation with Visual Prompt Tuning.

Beomyoung Kim, Joonsang Yu, Sung Ju Hwang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Gaussian Mixture Proposals with Pull-Push Learning Scheme to Capture Diverse Events for Weakly Supervised Temporal Video Grounding.

Sunoh Kim, Jungchan Cho, Joonsang Yu, Youngjoon Yoo, Jin Young Choi

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

GeNAS: Neural Architecture Search with Better Generalization.

Joonhyun Jeong, Joonsang Yu, Geondo Park, Dongyoon Han, Youngjoon Yoo

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Pipe-BD: Pipelined Parallel Blockwise Distillation.

Hongsun Jang, Jaewon Jung, Jaeyong Song, Joonsang Yu, Youngsok Kim, Jinho Lee

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

2022

Rediscovery of the Effectiveness of Standard Convolution for Lightweight Face Detection.

Joonhyun Jeong, Beomyoung Kim, Joonsang Yu, Youngjoon Yoo

CoRR, 2022

NN-LUT: neural approximation of non-linear operations for efficient transformer inference.

Joonsang Yu, Junki Park, Seongmin Park, Minsoo Kim, Sihwa Lee, Dong Hyun Lee, Jungwook Choi

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

Enabling hard constraints in differentiable neural network and accelerator co-exploration.

Deokki Hong, Kanghyun Choi, Hyeyoon Lee, Joonsang Yu, Noseong Park, Youngsok Kim, Jinho Lee

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher.

Kanghyun Choi, Hyeyoon Lee, Deokki Hong, Joonsang Yu, Noseong Park, Youngsok Kim, Jinho Lee

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

DANCE: Differentiable Accelerator/Network Co-Exploration.

Kanghyun Choi, Deokki Hong, Hojae Yoon, Joonsang Yu, Youngsok Kim, Jinho Lee

Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

2019

Acceleration of DNN Backward Propagation by Selective Computation of Gradients.

Gunhee Lee, Hanmin Park, Namhyung Kim, Joonsang Yu, Sujeong Jo, Kiyoung Choi

Proceedings of the 56th Annual Design Automation Conference 2019, 2019

Network Recasting: A Universal Method for Network Architecture Transformation.

Joonsang Yu, Sungbum Kang, Kiyoung Choi

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Tapered-Ratio Compression for Residual Network.

Sungbum Kang, Joonsang Yu, Kiyoung Choi

Proceedings of the International SoC Design Conference, 2018

2017

Efficient Low-Cost Fault-Localization and Self-Repairing Radix-2 Signed-Digit Adders Applying the Self-Dual Concept.

Hossein Moradian, Jeong-A Lee, Joonsang Yu

J. Signal Process. Syst., 2017

Hybrid spiking-stochastic Deep Neural Network.

Heesu Kim, Joonsang Yu, Kiyoung Choi

Proceedings of the 2017 International Symposium on VLSI Design, Automation and Test, 2017

A new stochastic mutiplier for deep neural networks.

Subin Huh, Joonsang Yu, Kiyoung Choi

Proceedings of the International SoC Design Conference, 2017

Accurate and Efficient Stochastic Computing Hardware for Convolutional Neural Networks.

Joonsang Yu, Kyounghoon Kim, Jongeun Lee, Kiyoung Choi

Proceedings of the 2017 IEEE International Conference on Computer Design, 2017

2016

A new approach to binarizing neural networks.

Jungwoo Seo, Joonsang Yu, Jongeun Lee, Kiyoung Choi

Proceedings of the International SoC Design Conference, 2016

Dynamic energy-accuracy trade-off using stochastic computing in deep neural networks.

Kyounghoon Kim, Jungki Kim, Joonsang Yu, Jungwoo Seo, Jongeun Lee, Kiyoung Choi

Proceedings of the 53rd Annual Design Automation Conference, 2016