Zobrazeno 1 - 10 of 16 pro vyhledávání: '"Eunseo Oh"'
1
Akademický článek
Brain–computer interface in critical care and rehabilitation
Autor: Eunseo Oh, Seyoung Shin, Sung-Phil Kim
Publikováno v: Acute and Critical Care, Vol 39, Iss 1, Pp 24-33 (2024)
This comprehensive review explores the broad landscape of brain–computer interface (BCI) technology and its potential use in intensive care units (ICUs), particularly for patients with motor impairments such as quadriplegia or severe brain injury.
Externí odkaz: https://doaj.org/article/7fc0595b9a594bab854f14fe55cbe2d1
Zobrazit plný text záznamu
2
Akademický článek
An Imbalanced Data Handling Framework for Industrial Big Data Using a Gaussian Process Regression-Based Generative Adversarial Network
Autor: Eunseo Oh, Hyunsoo Lee
Publikováno v: Symmetry, Vol 12, Iss 4, p 669 (2020)
The developments in the fields of industrial Internet of Things (IIoT) and big data technologies have made it possible to collect a lot of meaningful industrial process and quality-based data. The gathered data are analyzed using contemporary statist
Externí odkaz: https://doaj.org/article/70e14801d54d4432bc9317e8716de315
Zobrazit plný text záznamu
3
Akademický článek
Development of a Convolution-Based Multi-Directional and Parallel Ant Colony Algorithm Considering a Network with Dynamic Topology Changes
Autor: Eunseo Oh, Hyunsoo Lee
Publikováno v: Applied Sciences, Vol 9, Iss 18, p 3646 (2019)
While network path generation has been one of the representative Non-deterministic Polynomial-time (NP)-hard problems, changes of network topology invalidate the effectiveness of the existing metaheuristic algorithms. This research proposes a new and
Externí odkaz: https://doaj.org/article/4d6148d5389e4ca5a7b6b9aff3f1bccc
Zobrazit plný text záznamu
9
Development of a Convolution-Based Multi-Directional and Parallel Ant Colony Algorithm Considering a Network with Dynamic Topology Changes
Autor: Hyun-Soo Lee, Eunseo Oh
Publikováno v: Applied Sciences
Volume 9
Issue 18
Applied Sciences, Vol 9, Iss 18, p 3646 (2019)
While network path generation has been one of the representative Non-deterministic Polynomial-time (NP)-hard problems, changes of network topology invalidate the effectiveness of the existing metaheuristic algorithms. This research proposes a new and
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f04edff61730829c5d82dbba7eb68265
Zobrazit plný text záznamu
10
An Imbalanced Data Handling Framework for Industrial Big Data Using a Gaussian Process Regression-Based Generative Adversarial Network
Autor: Hyun-Soo Lee, Eunseo Oh
Publikováno v: Symmetry, Vol 12, Iss 669, p 669 (2020)
Symmetry
Volume 12
Issue 4
The developments in the fields of industrial Internet of Things (IIoT) and big data technologies have made it possible to collect a lot of meaningful industrial process and quality-based data. The gathered data are analyzed using contemporary statist
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c80c086a880a4a4b92ceb1d9b381114f
https://doi.org/10.3390/sym12040669
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje