Zobrazeno 1 - 10
of 1 615
pro vyhledávání: '"Byungjin AN"'
Autor:
Kweon, Sunjun, Choi, Byungjin, Chu, Gyouk, Song, Junyeong, Hyeon, Daeun, Gan, Sujin, Kim, Jueon, Kim, Minkyu, Park, Rae Woong, Choi, Edward
We present KorMedMCQA, the first Korean Medical Multiple-Choice Question Answering benchmark, derived from professional healthcare licensing examinations conducted in Korea between 2012 and 2024. The dataset contains 7,469 questions from examinations
Externí odkaz:
http://arxiv.org/abs/2403.01469
Reconstruction of unsteady vortical flow fields from limited sensor measurements is challenging. We develop machine learning methods to reconstruct flow features from sparse sensor measurements during transient vortex-airfoil wake interaction using o
Externí odkaz:
http://arxiv.org/abs/2305.05147
Extracting discriminative local features that are invariant to imaging variations is an integral part of establishing correspondences between images. In this work, we introduce a self-supervised learning framework to extract discriminative rotation-i
Externí odkaz:
http://arxiv.org/abs/2303.15472
Autor:
Byungjin AN, Takeo KAJISHIMA
Publikováno v:
Journal of Fluid Science and Technology, Vol 8, Iss 1, Pp 20-29 (2013)
Cavitation instability in the turbo-pump can be divided into two different stages: the local instability such as the rotating cavitation and the system instability such as the cavitation surge. In our study, a numerical analysis of cavitating flow in
Externí odkaz:
https://doaj.org/article/f1790d9862b9477cb746a45f8a68f3db
Autor:
Cho, Byungjin, Xiao, Yu
Offloading computation to nearby edge/fog computing nodes, including the ones carried by moving vehicles, e.g., vehicular fog nodes (VFN), has proved to be a promising approach for enabling low-latency and compute-intensive mobility applications, suc
Externí odkaz:
http://arxiv.org/abs/2209.01353
The rapid proliferation of learning systems in an arbitrarily changing environment mandates the need for managing tensions between exploration and exploitation. This work proposes a quantum-inspired bandit learning approach for the learning-and-adapt
Externí odkaz:
http://arxiv.org/abs/2208.07144
Autor:
Oh, Seyoung a, b, Kwon, Ojun a, b, Kim, Min Jeong a, b, Seo, Wondeok a, b, Cho, Eunjeong a, b, Park, Hyeon Ki d, Park, Woojin a, b, ⁎⁎, Cho, Byungjin a, b, c, ⁎
Publikováno v:
In Materials Science in Semiconductor Processing January 2025 185
Publikováno v:
In Composites Part B December 2024 287
Publikováno v:
In Molecules and Cells December 2024 47(12)
Autor:
LEE, Byungjin, SUNG, Sangkyung
Publikováno v:
In Chinese Journal of Aeronautics November 2024 37(11):335-354