Zobrazeno 1 - 10
of 79
pro vyhledávání: '"Sangmin Woo"'
Autor:
Jinyoung Choi, Hyunjoon Jeong, Sangmin Woo, Hyungmin Cho, Yohan Kim, Jeong-Taek Kong, Soyoung Kim
Publikováno v:
IEEE Journal of the Electron Devices Society, Vol 12, Pp 65-73 (2024)
The artificial neural network (ANN)-based compact model has significant advantages over physics-based standard compact models such as BSIM-CMG because it can achieve higher accuracy over a wide range of geometric parameters. This makes it particularl
Externí odkaz:
https://doaj.org/article/049f485f178443b79577e12895cf46a6
Autor:
Hyunjoon Jeong, Sangmin Woo, Jinyoung Choi, Hyungmin Cho, Yohan Kim, Jeong-Taek Kong, Soyoung Kim
Publikováno v:
IEEE Journal of the Electron Devices Society, Vol 11, Pp 153-160 (2023)
In this paper, we present a fast and expandable artificial neural network (ANN)-based compact model and parameter extraction flow to replace the existing complicated compact model implementation and model parameter extraction (MPE) method. In additio
Externí odkaz:
https://doaj.org/article/0cc50706c7ca472e91db8af1acef6556
Publikováno v:
Applied Sciences, Vol 12, Iss 3, p 1313 (2022)
Most neural machine translation models are implemented as a conditional language model framework composed of encoder and decoder models. This framework learns complex and long-distant dependencies, but its deep structure causes inefficiency in traini
Externí odkaz:
https://doaj.org/article/a840124518574967a7c46dd784f8628f
Autor:
Sangmin Woo, Hyojung Jung
Publikováno v:
Journal of Digital Contents Society. 22:1049-1057
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c84bcf78809620f93704d365d9130fa
https://doi.org/10.9728/dcs.2021.22.7.1049
https://doi.org/10.9728/dcs.2021.22.7.1049
Autor:
Sangmin Woo, Hyun Ho Park
Publikováno v:
The Journal of Korean Institute of Electromagnetic Engineering and Science. 31:651-654
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::163c93e9e2798937a5e65942de2c9fca
https://doi.org/10.5515/kjkiees.2020.31.7.651
https://doi.org/10.5515/kjkiees.2020.31.7.651
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c1063a6ba51a6dcab7473127d89a84c7
https://doi.org/10.2139/ssrn.4292746
https://doi.org/10.2139/ssrn.4292746
In multi-modal action recognition, it is important to consider not only the complementary nature of different modalities but also global action content. In this paper, we propose a novel network, named Modality Mixer (M-Mixer) network, to leverage co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c80d6d6698522ed103272479de6fbe86
Publikováno v:
Electronics; Volume 11; Issue 17; Pages: 2761
In this paper, we present an artificial neural network (ANN)-based compact model to evaluate the characteristics of a nanosheet field-effect transistor (NSFET), which has been highlighted as a next-generation nano-device. To extract data reflecting t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c9bf2b9bc201f8544af3b89f69782db
https://doi.org/10.3390/electronics11172761
https://doi.org/10.3390/electronics11172761
Publikováno v:
Electronics, Vol 10, Iss 989, p 989 (2021)
Electronics
Volume 10
Issue 9
Electronics
Volume 10
Issue 9
A common approach to jointly learn multiple tasks with a shared structure is to optimize the model with a combined landscape of multiple sub-costs. However, gradients derived from each sub-cost often conflicts in cost plateaus, resulting in a subpar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::334976fa4dcfc2c3fe28ee588856d536
https://www.mdpi.com/2079-9292/10/9/989
https://www.mdpi.com/2079-9292/10/9/989
In this work, we seek new insights into the underlying challenges of the Scene Graph Generation (SGG) task. Quantitative and qualitative analysis of the Visual Genome dataset implies -- 1) Ambiguity: even if inter-object relationship contains the sam
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c4ecb46e8f48f7a53817a69573d9a3a