Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Jun-Sik Choi"'
Autor:
Jun-Sik Choi
Publikováno v:
THE DAEGU HISTORICAL REVIEW. 145:137-177
Publikováno v:
Neural Networks. 115:1-10
Lung cancer is a global and dangerous disease, and its early detection is crucial for reducing the risks of mortality. In this regard, it has been of great interest in developing a computer-aided system for pulmonary nodules detection as early as pos
Publikováno v:
Journal of the Korean Institute of Illuminating and Electrical Installation Engineers. 32:20-26
Autor:
Jun Suk Oh1, Jun Sik Choi1, Young Hyuk Lee1, Kyung Og Ko1, Jae Woo Lim1, Eun Jung Cheon1, Gyung Min Lee1, Jung Min Yoon1 jmyoon@kyuh.ac.kr
Publikováno v:
Pediatric Gastroenterology, Hepatology & Nutrition. Dec2016, Vol. 19 Issue 4, p243-250. 8p.
Autor:
Jun Sik Choi1, Hyo Jeong Kim2 greatelena@naver.com
Publikováno v:
Journal of the Korean Child Neurology Society. Dec2016, Vol. 24 Issue 4, p240-245. 6p.
Autor:
김효정(Hyo Jeong Kim), 최준식(Jun Sik Choi)
Publikováno v:
Journal of the korean child neurology society. 24:240-245
목적: 인플루엔자는 호흡기 증상을 일으키는 흔한 원인이지만 드물게 심각한 신경학적 증상 또한 일으키는 것으로 알려져 있다. 본 연구에서는 2013년 계절성 인플루엔자 유행기간 동안 인
Autor:
Jun Sik Choi1, Kyung Og Ko1, Jae Woo Lim1, Eun Jeong Cheon1, Gyung Min Lee1, Jung Min Yoon1 jmyoon@kyuh.ac.kr
Publikováno v:
Pediatric Gastroenterology, Hepatology & Nutrition. Jun2016, Vol. 19 Issue 2, p110-115. 6p.
Autor:
Ji-Won Park, Ji Soo Kim, Jong-Ho Back, Jin-Seok Yeom, Jun-Sik Choi, Seong-Wook Jang, Gyu-Seong Shim, Hyun-Joong Kim
Publikováno v:
International Journal of Adhesion and Adhesives. 96:102445
Pressure-sensitive adhesives (PSAs) and UV-curable acrylic systems are widely utilized in different industries, with particular attention currently directed at their use in the production of re-useable modules for smart devices. Herein, we developed
Publikováno v:
2018 6th International Conference on Brain-Computer Interface (BCI).
In this paper, we propose a novel architecture of a deep neural network for EEG-based motor imagery classification. Unlike the existing deep neural networks in the literature, the proposed network allows us to analyze the learned network weights from
Publikováno v:
Machine Learning in Medical Imaging ISBN: 9783030009182
MLMI@MICCAI
MLMI@MICCAI
In this paper, we propose a novel method for MRI-based AD/MCI diagnosis that systematically integrates voxel-based, region-based, and patch-based approaches in a unified framework. Specifically, we parcellate a brain into predefined regions by using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87a5f9592d1aca9ff2114dca0d25be3d
https://doi.org/10.1007/978-3-030-00919-9_8
https://doi.org/10.1007/978-3-030-00919-9_8