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Sangwon Lee
Sangwon Lee
Bachelor's degree in 2018, Master's in 2020, School of Electronics Engineering, KNU.
Research interest: sound event detection (SED, applied to DCASE), audio source separation, medical image segmentation (PNI detection, PAIP challenge ). deep neural network design.
Email: lsw0767@knu.ac.kr
Publications
Publications
(Conference) Sangwon Lee, Youngjae Park, Jinhee Park, Giljin Jang, Hyemi Kim. Multi-target Learning on asymmetric U-Net for PNI boundary detection. In Proceedings of the 9th International Conference on Big Data Applications and Services (BIGDAS2021), Vol.9, No.1, Pages 127-131
Date and location: November 25-27, 2021; Jeju Island, Korea
DOI: https://doi.org/10.1109/ICTC52510.2021.9621001(Conference/Oral) Sangwon Lee, Gil-Jin Jang, Hyemi Kim. Asymmetric U-Net for Weakly Supervised Sound Event Detection. 한국인공지능학회 추계 학술대회
Date of Conference: November 4-6, 2021(Conference/Oral) Sangwon Lee, Gil-Jin Jang*. Stochastic Drop of Kernel Windows for Improved Generalization in Convolution Neural Networks. In Proceedings of the 2nd International Conference on Intelligent Human Systems Integration (IHSI 2019): Integrating People and Intelligent Systems, Pages 223-227, February, 2019.
Dates and Location: February 7-10, 2019, San Diego, California, USA
Presented: Saturday February 9, 2019, Session 2 8:30-10:30 (IHSI 2: Intelligence, Technology and Analytics I), http://ihsint.org/
DOI: https://doi.org/10.1007/978-3-030-11051-2_34(Conference/Oral) Sangwon Lee, Gil-Jin Jang*. Multi-Hop Global Average Pooling for Convolutional Neural Networks for Image Classification. In Proceedings of The Third International Conference On Consumer Electronics (ICCE) Asia, pages 248-251, June 2018.
Dates and Location: June 24 (Sun) - (Tue), 2018, Ramada Plaza Hotel, Jeju, Korea.
Presented: Tuesday, June 26, 2018, RS07 Image/Signal Processing.(Conference/Abstract/Poster) 오동훈, 강승태, 이상원, 장길진. 순환 신경망 앙상블 모델을 사용한 EMR 데이터 예측. 2018 뇌와 인공지능 심포지엄. pp. 159.
Donghoon Oh, Seungtae Kang, Sangwon Lee, Gil-Jin Jang. Ensemble Model-Based Prediction Using Recurrent Neural Networks for Electronic Medical Record. pp. 159.
Dates: January 30-31, 2018. Presented: January 31, 2018.(Conference) Sangwon Lee, Gil-Jin Jang. Recognition Model Based on Residual Networks for Cursive Hanja Recognition. International Conference on Information and Communication Technology Convergence (ICTC), Pages 580-584. 20 October 2017.
DOI: 10.1109/ICTC.2017.8190763
Presented: 20 Oct. 2017
Conference Location: Jeju Island, Korea (South)(Conference/Abstract/Poster) 오동훈, 강승태, 이상원, 장길진. 순환 신경망 앙상블 모델을 사용한 EMR 데이터 예측. 2018 뇌와 인공지능 심포지엄. pp. 159.
Donghoon Oh, Seungtae Kang, Sangwon Lee, Gil-Jin Jang. Ensemble Model-Based Prediction Using Recurrent Neural Networks for Electronic Medical Record. pp. 159.
Dates: January 30-31, 2018. Presented: January 31, 2018.
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