Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Gyeongdo Ham"'
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 3, p 035060 (2024)
Over the past decades, density functional theory (DFT) calculations have been utilized in various fields such as materials science and semiconductor devices. However, due to the inherent nature of DFT calculations, which rigorously consider interacti
Externí odkaz:
https://doaj.org/article/4c5310eb93b048adbe1d6abac9a721d7
Publikováno v:
IEEE Access, Vol 10, Pp 115652-115662 (2022)
Semi-supervised learning (SSL) methods for classification tasks exhibit a significant performance gain because they combine regularization and pseudo-labeling methods. General pseudo-labeling methods only depend on the model’s prediction when assig
Externí odkaz:
https://doaj.org/article/7d78423c5df8449daa63731787fdec7c
A Multiple‐State Ion Synaptic Transistor Applicable to Abnormal Car Detection with Transfer Learning
Autor:
Ji-Man Yu, Gyeongdo Ham, Chungryeol Lee, Jae-Hyeok Lee, Joon-Kyu Han, Jin-Ki Kim, Donggon Jang, Nahyun Kim, Moon-Seok Kim, Sung Gap Im, Dae-Shik Kim, Yang-Kyu Choi
Publikováno v:
Advanced Intelligent Systems, Vol 4, Iss 6, Pp n/a-n/a (2022)
An artificial synapse is an essential element to construct a hardware‐based artificial neural network (ANN). While various synaptic devices have been proposed along with studies on electrical characteristics and proper applications, a small number
Externí odkaz:
https://doaj.org/article/e94283a00f8b493fae6b6a045c28dc03
Publikováno v:
Pattern Recognition. 140:109541