Zobrazeno 1 - 10
of 126
pro vyhledávání: '"Il Seok Oh"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Due to the development of magnetic resonance (MR) imaging processing technology, image-based identification of endolymphatic hydrops (EH) has played an important role in understanding inner ear illnesses, such as Meniere’s disease or fluct
Externí odkaz:
https://doaj.org/article/4a7bc159bb074e35bcf0476f45f622c9
Publikováno v:
Agriculture, Vol 14, Iss 6, p 903 (2024)
In the realm of agricultural automation, the efficient management of tasks like yield estimation, harvesting, and monitoring is crucial. While fruits are typically detected using bounding boxes, pixel-level segmentation is essential for extracting de
Externí odkaz:
https://doaj.org/article/421542b7f0ad446899268bb3b68df160
Publikováno v:
Agriculture, Vol 13, Iss 11, p 2097 (2023)
Fruit trees in orchards are typically placed at equal distances in rows; therefore, their branches are intertwined. The precise segmentation of a target tree in this situation is very important for many agricultural tasks, such as yield estimation, p
Externí odkaz:
https://doaj.org/article/ed493a023f9346598f221433907e7c1c
Autor:
Il-Seok Oh, Jin-Seon Lee
Publikováno v:
IEEE Access, Vol 10, Pp 75571-75580 (2022)
A time series contain a large amount of information suitable for forecasting. Classical statistical and recent deep learning models have been widely used in a variety of forecasting applications. During the training data preparation stage, most model
Externí odkaz:
https://doaj.org/article/70ae4f8bb9aa407698d02aa9e5eef505
Autor:
Kang-Han Oh, Il-Seok Oh, Uyanga Tsogt, Jie Shen, Woo-Sung Kim, Congcong Liu, Nam-In Kang, Keon-Hak Lee, Jing Sui, Sung-Wan Kim, Young-Chul Chung
Publikováno v:
BMC Neuroscience, Vol 23, Iss 1, Pp 1-11 (2022)
Abstract Previous deep learning methods have not captured graph or network representations of brain structural or functional connectome data. To address this, we developed the BrainNet-Global Covariance Pooling-Attention Convolutional Neural Network
Externí odkaz:
https://doaj.org/article/d90ff5bedaa84ae7942aa4b27ff5d9cb
Publikováno v:
IEEE Access, Vol 10, Pp 94145-94157 (2022)
Preoperative planning is mandatory for successful total hip arthroplasty (THA). In planning, the operating surgeon should decide the best type and size of THA components for the patient. However, most digital templating software only simulates acetat
Externí odkaz:
https://doaj.org/article/e7cced2b42d9484a9e55eb0f2f3d057c
Publikováno v:
IEEE Access, Vol 8, Pp 8572-8582 (2020)
Recently, many methods to interpret and visualize deep neural network predictions have been proposed, and significant progress has been made. However, a more class-discriminative and visually pleasing explanation is required. Thus, this paper propose
Externí odkaz:
https://doaj.org/article/d42056f91bda4e8886d9574a8c54d2ce
Publikováno v:
IEEE Access, Vol 8, Pp 61433-61441 (2020)
Explaining the prediction of deep models has gained increasing attention to increase its applicability, even spreading it to life-affecting decisions. However there has been no attempt to pinpoint only the most discriminative features contributing sp
Externí odkaz:
https://doaj.org/article/a1271a8f2f154b23b7040d6f48dbadd3
Autor:
Kang-Han Oh, Il-Seok Oh, Uyanga Tsogt, Jie Shen, Woo-Sung Kim, Congcong Liu, Nam-In Kang, Keon-Hak Lee, Jing Sui, Sung-Wan Kim, Young-Chul Chung
Publikováno v:
BMC Neuroscience, Vol 23, Iss 1, Pp 1-1 (2022)
Externí odkaz:
https://doaj.org/article/ad3b6064335947ee81b3c79206650bf8
Publikováno v:
Applied Sciences, Vol 12, Iss 5, p 2288 (2022)
The segmentation algorithm of cerebrovascular magnetic resonance angiography (MRA) images based on deep learning plays an essential role in medical study. Traditional segmentation algorithms face poor segmentation results and poor connectivity when t
Externí odkaz:
https://doaj.org/article/f78ac356f1074e0cb71c313903167cb7