Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Hyeyeon Choi"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023)
Abstract Cone-beam computed tomography (CBCT) produces high-resolution of hard tissue even in small voxel size, but the process is associated with radiation exposure and poor soft tissue imaging. Thus, we synthesized a CBCT image from the magnetic re
Externí odkaz:
https://doaj.org/article/c821d01f7468441c93f27662caa0aed5
Publikováno v:
IEEE Access, Vol 11, Pp 129311-129319 (2023)
With the progressive automation of factories, the demand for deep learning methods capable of recognizing characters is rising. A billet identification number (BIN) is a string of characters that contains all information about the billet, but it is o
Externí odkaz:
https://doaj.org/article/5bdf7bfdbdee487091c26948948a0cad
Publikováno v:
IEEE Access, Vol 7, Pp 145095-145103 (2019)
This study proposes an automated brittle fracture rate (BFR) estimator using deep learning. As the demand for line-pipes increases in various industries, the need for BFR estimation through drop-weight tear test (DWTT) increases to evaluate steel's p
Externí odkaz:
https://doaj.org/article/e6e65e200db743b2aea6885ebafa913d
Publikováno v:
ACM Transactions on Intelligent Systems & Technology; Jun2024, Vol. 15 Issue 3, p1-20, 20p
Publikováno v:
IEEE Transactions on Industrial Informatics. 18:7686-7695
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c21524b48c7471a09ccbea3c5dd5de04
https://doi.org/10.1109/tii.2022.3147833
https://doi.org/10.1109/tii.2022.3147833
Publikováno v:
Applied Intelligence. 53:14233-14248
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::79cc421579ee666d5377d0a06b295cc3
https://doi.org/10.1007/s10489-022-04207-7
https://doi.org/10.1007/s10489-022-04207-7
Autor:
Wonseok Jeong, Hyeyeon Choi, Bum Jun Kim, Hyeonah Jang, Dong Gu Lee, Donggeon Lee, Sang Woo Kim
Publikováno v:
2022 22nd International Conference on Control, Automation and Systems (ICCAS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35aa0d7ed60dd27599037e7d66649cd1
https://doi.org/10.23919/iccas55662.2022.10003768
https://doi.org/10.23919/iccas55662.2022.10003768
Publikováno v:
ISIJ International. 59:98-103
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa770b47ccd4b2f208d9940a0ae0ce33
https://doi.org/10.2355/isijinternational.isijint-2018-506
https://doi.org/10.2355/isijinternational.isijint-2018-506
Publikováno v:
IEEE Access, Vol 7, Pp 145095-145103 (2019)
This study proposes an automated brittle fracture rate (BFR) estimator using deep learning. As the demand for line-pipes increases in various industries, the need for BFR estimation through drop-weight tear test (DWTT) increases to evaluate steel's p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e7d8520215a81a7d4f18d2115bffdf9
https://ieeexplore.ieee.org/document/8859257/
https://ieeexplore.ieee.org/document/8859257/
Deep neural networks have been used in various fields, but their internal behavior is not well known. In this study, we discuss two counterintuitive behaviors of convolutional neural networks (CNNs). First, we evaluated the size of the receptive fiel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1817ee2542fb68d15bedf66466ab2bec
