Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Gyemin Lee"'
Publikováno v:
Frontiers in Psychology, Vol 14 (2023)
This research aims to explore the determinants of the League of Legends Champions Korea (LCK) highlight views and comment counts. The data of 629 game highlight views and comment counts for seven tournaments were collected from YouTube. The highlight
Externí odkaz:
https://doaj.org/article/90577631a28144f88bc86f987bf1875e
Autor:
Gyemin Lee
Publikováno v:
Symmetry, Vol 7, Iss 3, Pp 1164-1175 (2015)
This paper presents a novel hierarchical clustering method using support vector machines. A common approach for hierarchical clustering is to use distance for the task. However, different choices for computing inter-cluster distances often lead to fa
Externí odkaz:
https://doaj.org/article/d31255c3a36c45f38be5215afc85daa7
Autor:
JoonHo Lee, Gyemin Lee
Publikováno v:
Neural Networks. 161:682-692
Most unsupervised domain adaptation (UDA) methods assume that labeled source images are available during model adaptation. However, this assumption is often infeasible owing to confidentiality issues or memory constraints on mobile devices. Some rece
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::805d94ecc18014fa91a9c24542295a83
https://doi.org/10.1016/j.neunet.2023.02.009
https://doi.org/10.1016/j.neunet.2023.02.009
Autor:
Dong-Hyun Kim, Gyemin Lee
Publikováno v:
Journal of the Korean Data And Information Science Society. 33:1043-1052
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::625fb837b64dd996d755caeb22ac2cb8
https://doi.org/10.7465/jkdi.2022.33.6.1043
https://doi.org/10.7465/jkdi.2022.33.6.1043
Autor:
JoonHo Lee, Gyemin Lee
Publikováno v:
International Workshop on Advanced Imaging Technology (IWAIT) 2023.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6957d431aab288a09476ccf0f48bdd2e
https://doi.org/10.1117/12.2666906
https://doi.org/10.1117/12.2666906
Autor:
JoonHo Lee, Gyemin Lee
Unsupervised domain adaptation (UDA) aims to improve the prediction performance in the target domain under distribution shifts from the source domain. The key principle of UDA is to minimize the divergence between the source and the target domains. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed544f69eb2bbee974f4086b773ad7e9
http://arxiv.org/abs/2211.08866
http://arxiv.org/abs/2211.08866
Publikováno v:
Current Applied Physics. 19:856-865
The purpose of this study is to optimize the collimator mask design for the rotational modulation collimator (RMC) imaging system. First, we optimized the slat and slit width of the collimator mask which affects the number of particles entering the d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7692619179e2f83f38ad9054b1719119
https://doi.org/10.1016/j.cap.2019.03.021
https://doi.org/10.1016/j.cap.2019.03.021
Autor:
Hansol Lee, Gyemin Lee
Publikováno v:
ICIP
In this paper, we propose a novel supervised method for summarizing long-length videos. Many recent approaches presented promising results in video summarization. However, videos in most benchmark datasets are short in duration $(\lt 10$ minutes), an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1266c8024c5524b97bb1b5b63f6b105
https://doi.org/10.1109/icip40778.2020.9190636
https://doi.org/10.1109/icip40778.2020.9190636
Autor:
Gyemin Lee, JoonHo Lee
Publikováno v:
ICIP
The key principle of unsupervised domain adaptation is to minimize the divergence between source and target domain. Many recent methods follow this principle to learn domaininvariant features. They train task-specific classifiers to maximize the dive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76abe35b67e6b39c592433df3b0a6bdd
https://doi.org/10.1109/icip40778.2020.9190738
https://doi.org/10.1109/icip40778.2020.9190738
Publikováno v:
Environmental Geochemistry and Health. 41:357-380
The CO2-rich spring water (CSW) occurring naturally in three provinces, Kangwon (KW), Chungbuk (CB), and Gyeongbuk (GB) of South Korea was classified based on its hydrochemical properties using compositional data analysis. Additionally, the geochemic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d155e5e6d09c828aa4b271830c86d836
https://doi.org/10.1007/s10653-017-0057-9
https://doi.org/10.1007/s10653-017-0057-9