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AI Challenge Participation
AI Challenge Participation
MOAI MCRC Deep Learning Challenge for urinary stone challenge
MOAI MCRC Deep Learning Challenge for urinary stone challenge
Wonkwang Research Institute of Medical & Life Convergence, South Korea, Seoul
Develop AI segmentation algorithm for Urinary stone on NECT imaging
Won 3rd place
MOAI 2020 Body Morphometry AI Segmentation Online Challenge
MOAI 2020 Body Morphometry AI Segmentation Online Challenge
Wonkwang Research Institute of Medical & Life Convergence, South Korea, Seoul
Develop AI segmentation algorithm for body morphometry segmentation on CT imaging.
Won 2nd place
Korea Health Datathon 2020
Korea Health Datathon 2020
Konyang University Hospital, Department of Artificial Intelligence at Konyang University, South Korea, Seoul
Develop maxillary sinusitis auto detection system based on deep learning using sinusitis x-ray images.
Won 3rd place
Workshop Instructor/TA at Deep Learning Section
Workshop Instructor/TA at Deep Learning Section
Biomedical Data Science Workshop
Biomedical Data Science Workshop
Yonsei University College of Medicine, South Korea, Seoul
Participated as a instructor and delivered lecture to medical doctors in Severance on a topic of deep-learning based image classification
Medical AI Specialist Training Course
Medical AI Specialist Training Course
Korea Human Resource Development Institute for Health & Welfare, South Korea, Seoul
Participated as Teaching Assistant and assisted medical doctors on running deep learning tutorial codes using Jupyter Notebook.
Paper Reviews
Paper Reviews
Do wide and deep networks learn the same things? Uncovering how neural network representations vary with width and depth, arxiv, 2020 (Paper , Review )
End-to-End Object Detection with Transformers, ECCV, 2020 ( Paper, Review )
How useful is self-supervised pretraining for Visual tasks?, CVPR, 2020 ( Paper, Review )
A Simple Framework for Contrastive Learning of Visual Representations, ICML, 2020 ( Paper, Review )
Your Classifier is Secretly an Energy based model and you should treat it like one, ICLR, 2020 ( Paper, Review )
An annotation sparsification strategy for 3D medical image segmentation via representative selection and self-training, AAAI, 2020 (Paper, Review )
DeepStrip: High Resolution Boundary Refinement, CVPR, 2020 ( Paper, Review )
ResNeSt: Split-Attention Networks, CVPR, 2020 ( Paper, Review )
Learning Sparse Networks using Targeted Dropout, Neurips, 2018 ( Paper, Review )
Progressive learning and Disentanglement of hierarchical representations, ICLR, 2020 ( Paper, Review )
Segmenting Medical MRI via Recurrent Decoding Cell, AAAI, 2020 ( Paper, Review )
Deep Generative model-based quality control for cardiac MRI segmentation, MICCAI, 2020 ( Paper, Review )
Large Scale GAN Training for High Fidelity Natural Image Synthesis, ICLR, 2019 ( Paper, Review )
Mix Conv: Mixed Depthwise Convolutional Kernels, BMVC, 2019 ( Paper, Review )
FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference, CVPR, 2019 ( Paper, Review )
A Probabilistic U-Net for Segmentation of Ambiguous Images, NIPS, 2018 ( Paper, Review )
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