Hyeonseob Nam
Hyeonseob Nam
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Няма потвърден имейл адрес - Начална страница
Learning multi-domain convolutional neural networks for visual tracking
H Nam, B Han
Proceedings of the IEEE conference on computer vision and pattern …, 2016
The visual object tracking vot2015 challenge results
M Kristan, J Matas, A Leonardis, M Felsberg, L Cehovin, G Fernandez, ...
Proceedings of the IEEE international conference on computer vision …, 2015
Dual attention networks for multimodal reasoning and matching
H Nam, JW Ha, J Kim
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017
Modeling and propagating cnns in a tree structure for visual tracking
H Nam, M Baek, B Han
arXiv preprint arXiv:1608.07242, 2016
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
Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study
HE Kim, HH Kim, BK Han, KH Kim, K Han, H Nam, EH Lee, EK Kim
The Lancet Digital Health 2 (3), e138-e148, 2020
Srm: A style-based recalibration module for convolutional neural networks
HJ Lee, HE Kim, H Nam
Proceedings of the IEEE/CVF International conference on computer vision …, 2019
Batch-instance normalization for adaptively style-invariant neural networks
H Nam, HE Kim
Advances in Neural Information Processing Systems 31, 2018
The thermal infrared visual object tracking VOT-TIR2015 challenge results
M Felsberg, A Berg, G Hager, J Ahlberg, M Kristan, J Matas, A Leonardis, ...
Proceedings of the ieee international conference on computer vision …, 2015
Online graph-based tracking
H Nam, S Hong, B Han
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
Intra-class contrastive learning improves computer aided diagnosis of breast cancer in mammography
K You, S Lee, K Jo, E Park, T Kooi, H Nam
International Conference on Medical Image Computing and Computer-Assisted …, 2022
Transformer-based deep neural network for breast cancer classification on digital breast tomosynthesis images
W Lee, H Lee, H Lee, EK Park, H Nam, T Kooi
Radiology: Artificial Intelligence 5 (3), e220159, 2023
Robust artificial intelligence-powered imaging biomarker based on mammography for risk prediction of breast cancer.
EK Park, H Lee, M Kim, KH Kim, H Nam, Y Chang, S Ryu
Journal of Clinical Oncology 40 (16_suppl), 10533-10533, 2022
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