Sungroh Yoon – Page 19 – Data Science & Artificial Intelligence Laboratory

Category / Sungroh Yoon

Joint Contrastive Learning for Unsupervised Domain Adaptation

Changhwa Park, Jonghyun Lee, Jaeyoon Yoo, Minhoe Hur, Sungroh Yoon, arXiv:2006.10297 [cs.CV], June 2020.
paper link

18 June 2020

Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization

Saehyung Lee, Hyungyu Lee, Sungroh Yoon, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Oral Presentation, pp. 272-281, Seattle, USA, June 2020.
paper slides link arXiv suppl

16 June 2020

Conference, Sungroh Yoon

Automated facies identification using unsupervised clustering

Youngjun Hong, Shinjo Wang, Jeehoon Bae, Jaeyoon Yoo, Sungroh Yoon, Offshore Technology Conference (OTC), Houston, USA, May 2020.
paper link

04 May 2020

Conference, Sungroh Yoon

Anomaly Detection by Learning Dynamics from a Graph

Jaekoo Lee, Ho Bae, Sungroh Yoon, IEEE Access, vol. 8, no. 1, pp. 64356-64365, March 2020.
paper link

30 March 2020

Journal, Sungroh Yoon

Energy-aware Placement for SRAM-NVM Hybrid FPGAs

Seongsik Park, Jongwan Kim, Sungroh Yoon, in Proceedings of Design, Automation and Test in Europe (DATE), pp. 858-863, Grenoble, France, March 2020.
paper link

09 March 2020

Conference, Sungroh Yoon

Spiking-YOLO: Spiking Neural Network for Energy-efficient Object Detection

Seijoon Kim, Seongsik Park, Byunggook Na, Sungroh Yoon, in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), vol. 34, no. 7, pp. 11270-11277, New York, USA, February 2020.
paper link arXiv

10 February 2020

Conference, Sungroh Yoon

High-throughput analysis of the activities of xCas9, SpCas9-NG and SpCas9 at matched and mismatched target sequences in human cells

Hui Kwon Kim, Sungtae Lee, Younggwang Kim, Jinman Park, Seonwoo Min, Jae Woo Choi, Tony P Huang, Sungroh Yoon, David R Liu, Hyongbum Henry Kim, Nature Biomedical Engineering, vol. 4, pp. 111-124, January 2020.
paper link

14 January 2020

Journal, Seonwoo Min, Sungroh Yoon

AnomiGAN: Generative adversarial networks for anonymizing private medical data

Ho Bae, Dahuin Jung, Hyun-Soo Choi, Sungroh Yoon, in Proceedings of Pacific Symposium on Biocomputing (PSB), vol. 25, pp. 563-574, Hawaii, USA, January 2020.
paper link arXiv

03 January 2020

Conference, Sungroh Yoon

End-to-End Blood Pressure Prediction via Fully Convolutional Networks

Sanghyun Baek, Jiyong Jang, Sungroh Yoon, IEEE Access, vol. 7, no. 1, pp. 185458-185468, December 2019.
paper link

31 December 2019

Journal, Sungroh Yoon

Prediction of Drug Classes with a Deep Neural Network using Drug Targets and Chemical Structure Data

Jeonghee Jo, Hyun-Soo Choi, Sungroh Yoon, in Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), San Diego, USA, November 2019.
preprint link

18 November 2019

Conference, Sungroh Yoon, 미분류

Category / Sungroh Yoon

Joint Contrastive Learning for Unsupervised Domain Adaptation

Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization

Automated facies identification using unsupervised clustering

Anomaly Detection by Learning Dynamics from a Graph

Energy-aware Placement for SRAM-NVM Hybrid FPGAs

Spiking-YOLO: Spiking Neural Network for Energy-efficient Object Detection

High-throughput analysis of the activities of xCas9, SpCas9-NG and SpCas9 at matched and mismatched target sequences in human cells

AnomiGAN: Generative adversarial networks for anonymizing private medical data

End-to-End Blood Pressure Prediction via Fully Convolutional Networks

Prediction of Drug Classes with a Deep Neural Network using Drug Targets and Chemical Structure Data

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