Conference – Data Science & Artificial Intelligence Laboratory

Category / Conference

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), Seattle, USA, June 2020.
preprint slides link

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.
link

04 May 2020

Conference, Sungroh Yoon

Augmented Machine Learning Approach of Rate of Penetration Prediction for North Sea Oilfield

Youngjun Hong, Jaeyoon Yoo, Shinjo Wang, Sungroh Yoon, Offshore Technology Conference (OTC) Asia, Kuala Lumpur, Malaysia, March 2020.
link

24 March 2020

Conference, 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), Grenoble, France, March 2020.
preprint 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), New York, USA, February 2020.
preprint link arXiv

10 February 2020

Conference, 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

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

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation

Jungbeom Lee, Eunji Kim, Sungmin Lee, Jangho Lee, Sungroh Yoon, in Proceedings of IEEE International Conference on Computer Vision (ICCV), Seoul, Korea, October 2019.
paper link arXiv

27 October 2019

Conference, Sungroh Yoon

Mutual Suppression Network for Video Prediction using Disentangled Features

Jungbeom Lee, Jangho Lee, Sungmin Lee, Sungroh Yoon, in Proceedings of British Machine Vision Conference (BMVC), Cardiff, UK, September 2019.
paper arXiv arXiv

09 September 2019

Conference, Sungroh Yoon

HexaGAN: Generative Adversarial Nets for Real World Classification

Uiwon Hwang, Dahuin Jung, Sungroh Yoon, in Proceedings of International Conference on Machine Learning (ICML), Long Beach, CA, USA, June 2019.
paper slides link arXiv suppl

30 June 2019

Conference, Sungroh Yoon

Category / Conference

Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization

Automated facies identification using unsupervised clustering

Augmented Machine Learning Approach of Rate of Penetration Prediction for North Sea Oilfield

Energy-aware Placement for SRAM-NVM Hybrid FPGAs

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

AnomiGAN: Generative adversarial networks for anonymizing private medical data

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

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation

Mutual Suppression Network for Video Prediction using Disentangled Features

HexaGAN: Generative Adversarial Nets for Real World Classification

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