Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Wonjong Rhee"'
Autor:
Soonil Kwon, Jangwon Suh, Eue-Keun Choi, Jimyeong Kim, Hojin Ju, Hyo-Jeong Ahn, Sunhwa Kim, So-Ryoung Lee, Seil Oh, Wonjong Rhee
Publikováno v:
Digital Health, Vol 10 (2024)
Background Obtaining tachycardia electrocardiograms (ECGs) in patients with paroxysmal supraventricular tachycardia (PSVT) is often challenging. Sinus rhythm ECGs are of limited predictive value for PSVT types in patients without preexcitation. This
Externí odkaz:
https://doaj.org/article/cda34f5328df4369a858271c91a8a08a
Publikováno v:
IEEE Access, Vol 12, Pp 159877-159888 (2024)
The latest advancements in unsupervised learning of sentence embeddings predominantly involve employing contrastive learning-based (CL-based) fine-tuning over pre-trained language models. In this study, we analyze the latest sentence embedding method
Externí odkaz:
https://doaj.org/article/ff9de3745a8043e090fcc51665355ebf
Publikováno v:
IEEE Access, Vol 11, Pp 25467-25479 (2023)
Multiple gas detection in mixed-gas environments is a challenging issue in many engineering industries because some of the gases can raise defect rates and reduce production efficiency. For chemo-resistive gas sensors, a precise estimation can be cha
Externí odkaz:
https://doaj.org/article/8df189b8b16343d8917e10d0762a2cd2
Recent advances in audio understanding tasks leverage the reasoning capabilities of LLMs. However, adapting LLMs to learn audio concepts requires massive training data and substantial computational resources. To address these challenges, Retrieval-Au
Externí odkaz:
http://arxiv.org/abs/2410.10913
Autor:
Eunjung Lee, Wonjong Rhee
Publikováno v:
IEEE Access, Vol 9, Pp 15413-15425 (2021)
While the general belief is that the best way to predict electric load is through individualized models, the existing studies have focused on one-for-all models because the individual models are difficult to train and require a significantly larger d
Externí odkaz:
https://doaj.org/article/4ccb201e6ea84230858360758eee3b47
Publikováno v:
IEEE Access, Vol 9, Pp 54739-54756 (2021)
In modern transportation systems, an enormous amount of traffic data is generated every day. This has led to rapid progress in short-term traffic prediction (STTP), in which deep learning methods have recently been applied. In traffic networks with c
Externí odkaz:
https://doaj.org/article/3c6fabaa10574fbf8ae850f8a8f45542
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:
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
Publikováno v:
Energies, Vol 12, Iss 9, p 1696 (2019)
Energy disaggregation, or nonintrusive load monitoring (NILM), is a technology for separating a household’s aggregate electricity consumption information. Although this technology was developed in 1992, its practical usage and mass deployment have
Externí odkaz:
https://doaj.org/article/23264556ea374bf4a4c70818d7c2b843
Publikováno v:
Neural Networks. 161:165-177
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9168f92ab5d0864ee56b9a1f62bdb21
https://doi.org/10.1016/j.neunet.2023.01.024
https://doi.org/10.1016/j.neunet.2023.01.024