Zobrazeno 1 - 10
of 58
pro vyhledávání: '"DaeYoung Choi"'
Publikováno v:
Veterinary Sciences, Vol 11, Iss 7, p 325 (2024)
In the context of veterinary medicine, minimally invasive techniques for feline spinal surgery remain underexplored, particularly for percutaneous laser disc ablation (PLDA) when using the Holmium:YAG (Ho:YAG) laser. This study aimed to refine the ap
Externí odkaz:
https://doaj.org/article/439f1a9032e3450dbef6f4ef015dcf7b
Publikováno v:
IEEE Access, Vol 8, Pp 52588-52608 (2020)
Compared to the traditional machine learning models, deep neural networks (DNN) are known to be highly sensitive to the choice of hyperparameters. While the required time and effort for manual tuning has been rapidly decreasing for the well developed
Externí odkaz:
https://doaj.org/article/fa0c3838896944bb8a7d31180eaa345f
Publikováno v:
IEEE Access, Vol 6, Pp 7713-7718 (2018)
The sciatic nerve is the longest and widest single nerve in the human body and is responsible for the signal transduction of the entire hind limb region. Its wide nerve dynamic range and size makes it sensitive to injury. The branching and location o
Externí odkaz:
https://doaj.org/article/b6a12163dd134a86b4690f8e872d60a7
Publikováno v:
PLoS ONE, Vol 12, Iss 7, p e0180735 (2017)
Internet-connected devices, especially mobile devices such as smartphones, have become widely accessible in the past decade. Interaction with such devices has evolved into frequent and short-duration usage, and this phenomenon has resulted in a perva
Externí odkaz:
https://doaj.org/article/944432575a024ab88ddfef3014a6d8f2
Autor:
Daeyoung Choi, Seung Hyun Paik, Young-Kyu Kim, Jong-Ho Yoo, SangWoo Jung, Tae-Hwan Kim, Dae-Nyeon Kim
Publikováno v:
The Journal of Korean Institute of Information Technology. 20:75-81
Publikováno v:
The Journal of Korean Institute of Information Technology. 20:83-90
Autor:
Woosung Jung, Jong-Hoi Cho, SungHun Lim, TaeSeop Lee, DaeYoung Choi, Jong-Hyun Seo, SeungHyun Lee, JunKyoung Lee, You Jin Kim, Jeong Ho Yeo, Alex Brikker, Roi Meir, Ran Alkoken, Kyeongju Han, Sujin Lim, KyungJae Choi, Chanhee Kwak, Hyeon Sang Shin
Publikováno v:
Metrology, Inspection, and Process Control XXXVII.
Publikováno v:
The Journal of Korean Institute of Information Technology. 19:115-121
Publikováno v:
The Journal of Korean Institute of Information Technology. 19:45-52
Publikováno v:
IEEE Access, Vol 8, Pp 52588-52608 (2020)
Compared to the traditional machine learning models, deep neural networks (DNN) are known to be highly sensitive to the choice of hyperparameters. While the required time and effort for manual tuning has been rapidly decreasing for the well developed