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Jongchan Park
Jongchan Park
Lunit Inc.
Verified email at lunit.io - Homepage
Title
Cited by
Cited by
Year
CBAM: Convolutional Block Attention Module
S Woo, J Park, JY Lee, IS Kweon
Proceedings of the European conference on computer vision (ECCV), 3-19, 2018
200322018
BAM: Bottleneck Attention Module
J Park, S Woo, JY Lee, IS Kweon
Proceedings of the British Machine Vision Conference, 2018
14662018
Reducing Domain Gap by Reducing Style Bias
H Nam, HJ Lee, J Park, W Yoon, D Yoo
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
401*2021
Distort-and-recover: Color enhancement using deep reinforcement learning
J Park, JY Lee, D Yoo, IS Kweon
Proceedings of the IEEE conference on computer vision and pattern …, 2018
2292018
A simple and light-weight attention module for convolutional neural networks
J Park, S Woo, JY Lee, IS Kweon
International journal of computer vision 128 (4), 783-798, 2020
882020
Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs
JG Nam, M Kim, J Park, EJ Hwang, JH Lee, JH Hong, JM Goo, CM Park
European Respiratory Journal 57 (5), 2021
772021
CBAM: convolutional block attention module (2018)
S Woo, J Park, JY Lee, IS Kweon
arXiv preprint arXiv:1807.06521, 1807
561807
Pt4al: Using self-supervised pretext tasks for active learning
JSK Yi, M Seo, J Park, DG Choi
European conference on computer vision, 596-612, 2022
332022
Studying the effects of self-attention for medical image analysis
A Rao, J Park, S Woo, JY Lee, O Aalami
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
312021
Unsupervised change detection based on image reconstruction loss
H Noh, J Ju, M Seo, J Park, DG Choi
proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
282022
Evaluation of a deep learning-based computer-aided detection algorithm on chest radiographs: Case–control study
SY Choi, S Park, M Kim, J Park, YR Choi, KN Jin
Medicine 100 (16), e25663, 2021
212021
Learning visual context by comparison
M Kim, J Park, S Na, CM Park, D Yoo
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
162020
A self-supervised sampler for efficient action recognition: Real-world applications in surveillance systems
M Seo, D Cho, S Lee, J Park, D Kim, J Lee, J Ju, H Noh, DG Choi
IEEE Robotics and Automation Letters 7 (2), 1752-1759, 2021
92021
Apparatus for predicting metadata of medical image and method thereof
J Park, D Yoo
US Patent 10,824,908, 2020
42020
Training method for specializing artificial interlligence model in institution for deployment, and apparatus for training artificial intelligence model
D Yoo, P Seungwook, M Kim, J Park
US Patent App. 17/689,196, 2022
32022
Deep learning-based ensemble model using hematoxylin and eosin (H&E) whole slide images (WSIs) for the prediction of MET mutations in non-small cell lung cancer (NSCLC).
YL Choi, S Park, HA Jung, JM Sun, SH Lee, JS Ahn, MJ Ahn, T Lee, ...
Journal of Clinical Oncology 41 (16_suppl), e13578-e13578, 2023
22023
Apparatus for predicting metadata of medical image and method thereof
J Park, D Yoo
US Patent App. 17/685,740, 2022
22022
Apparatus and method for processing medical image using predicted metadata
JC Park, DG Yoo, KH You, HS Nam, HJ Lee, SH Lee
US Patent 11,978,548, 2024
12024
Method for filtering normal medical image, method for interpreting medical image, and computing device implementing the methods
J Park
US Patent 11,928,817, 2024
2024
Method for filtering normal medical image, method for interpreting medical image, and computing device implementing the methods
J Park
US Patent 11,574,727, 2023
2023
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