Zobrazeno 1 - 10
of 31 499
pro vyhledávání: '"Kim, Hyung"'
Autor:
Kim, Inkoo, Jeong, Daun, Weisburn, Leah, Alexiu, Alexandra, Van Voorhis, Troy, Rhee, Young Min, Son, Won-Joon, Kim, Hyung-Jin, Yim, Jinkyu, Kim, Sungmin, Cho, Yeonchoo, Jang, Inkook, Lee, Seungmin, Kim, Dae Sin
Modern graphics processing units (GPUs) provide an unprecedented level of computing power. In this study, we present a high-performance, multi-GPU implementation of the analytical nuclear gradient for Kohn-Sham time-dependent density functional theor
Externí odkaz:
http://arxiv.org/abs/2407.16586
Monocular 3D object detection is an important challenging task in autonomous driving. Existing methods mainly focus on performing 3D detection in ideal weather conditions, characterized by scenarios with clear and optimal visibility. However, the cha
Externí odkaz:
http://arxiv.org/abs/2407.16448
While federated learning leverages distributed client resources, it faces challenges due to heterogeneous client capabilities. This necessitates allocating models suited to clients' resources and careful parameter aggregation to accommodate this hete
Externí odkaz:
http://arxiv.org/abs/2407.03086
Autor:
Han, Subin, Kim, Hyung Do
Discovery of the Higgs boson decay to dimuon is anticipated soon based on the current evidence. Precise categorization of the events without affecting the invariant mass shape is crucial in the analysis. Decorrelation of the invariant mass and the ou
Externí odkaz:
http://arxiv.org/abs/2406.11961
Computer vision applications predict on digital images acquired by a camera from physical scenes through light. However, conventional robustness benchmarks rely on perturbations in digitized images, diverging from distribution shifts occurring in the
Externí odkaz:
http://arxiv.org/abs/2404.15882
Recently, foundation models trained on massive datasets to adapt to a wide range of tasks have attracted considerable attention and are actively being explored within the computer vision community. Among these, the Segment Anything Model (SAM) stands
Externí odkaz:
http://arxiv.org/abs/2403.09199
Safe Multi-agent reinforcement learning (safe MARL) has increasingly gained attention in recent years, emphasizing the need for agents to not only optimize the global return but also adhere to safety requirements through behavioral constraints. Some
Externí odkaz:
http://arxiv.org/abs/2403.06397
Autor:
Heo, JoonNyung, Park, Ji Ae, Han, Deokjae, Kim, Hyung-Jun, Ahn, Daeun, Ha, Beomman, Seog, Woong, Park, Yu Rang
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 11, p e22131 (2020)
BackgroundCOVID-19 has officially been declared as a pandemic, and the spread of the virus is placing sustained demands on public health systems. There are speculations that the COVID-19 mortality differences between regions are due to the disparitie
Externí odkaz:
https://doaj.org/article/8137518358a940139db2129ebf134ee2
Autor:
Heo, JoonNyung, Sung, MinDong, Yoon, Sangchul, Jang, Jinkyu, Lee, Wonwoo, Han, Deokjae, Kim, Hyung-Jun, Kim, Han-Kyeol, Han, Ji Hyuk, Seog, Woong, Ha, Beomman, Park, Yu Rang
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 11, p e19665 (2020)
BackgroundClear guidelines for a patient with suspected COVID-19 infection are unavailable. Many countries rely on assessments through a national hotline or telecommunications, but this only adds to the burden of an already overwhelmed health care sy
Externí odkaz:
https://doaj.org/article/78ec7dc631d64c15bbce54f488c0ffd8
Autor:
Kim, Hyung-Jun, Han, Deokjae, Kim, Jeong-Han, Kim, Daehyun, Ha, Beomman, Seog, Woong, Lee, Yeon-Kyeng, Lim, Dosang, Hong, Sung Ok, Park, Mi-Jin, Heo, JoonNyung
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 11, p e24225 (2020)
BackgroundPrioritizing patients in need of intensive care is necessary to reduce the mortality rate during the COVID-19 pandemic. Although several scoring methods have been introduced, many require laboratory or radiographic findings that are not alw
Externí odkaz:
https://doaj.org/article/a6e8de23cebc431e8fb5de32c60509c7