Zobrazeno 1 - 10
of 105
pro vyhledávání: '"Jong-Pil Yun"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Developing a deep-learning-based diagnostic model demands extensive labor for medical image labeling. Attempts to reduce the labor often lead to incomplete or inaccurate labeling, limiting the diagnostic performance of models. This paper (i)
Externí odkaz:
https://doaj.org/article/969fc6d239734b5dace34699cb42be4e
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-8 (2023)
Abstract This study suggests a hybrid method based on ResNet50 and vision transformer (ViT) in an age estimation model. To this end, panoramic radiographs are used for learning by considering both local features and global information, which is impor
Externí odkaz:
https://doaj.org/article/b908198c18ca4123abcb0603878ba706
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
Autor:
WooSang Shin, Han-Gyeol Yeom, Ga Hyung Lee, Jong Pil Yun, Seung Hyun Jeong, Jong Hyun Lee, Hwi Kang Kim, Bong Chul Kim
Publikováno v:
BMC Oral Health, Vol 21, Iss 1, Pp 1-7 (2021)
Abstract Background Posteroanterior and lateral cephalogram have been widely used for evaluating the necessity of orthognathic surgery. The purpose of this study was to develop a deep learning network to automatically predict the need for orthodontic
Externí odkaz:
https://doaj.org/article/d071e29b844a4fad83981b75ebeb7dcf
Publikováno v:
IEEE Access, Vol 9, Pp 98962-98972 (2021)
This paper constructs an explainable neural network model for fault diagnosis with a 1D vibration signal of equipment and proposes an explainable method with a frequency activation map of the proposed model. The frequency activation map visualizes th
Externí odkaz:
https://doaj.org/article/21be685b870043b4a3e67b08421306a3
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 8350-8358 (2021)
In this article, a multichannel convolutional neural network (CNN) based object detection was used to detect suspected trees of pine wilt disease after acquiring aerial photographs through a rotorcraft drone equipped with a multispectral camera. The
Externí odkaz:
https://doaj.org/article/12158f9a043c4b05b7746bc2e5e6be5d
Publikováno v:
IEEE Access, Vol 9, Pp 136552-136560 (2021)
A convolutional neural network (CNN) based regression is proposed for estimating the brittle fracture ratio (BFR) in a fracture image of a drop weight tear test (DWTT) specimen. Different with the previous complex semantic segmentation-based estimato
Externí odkaz:
https://doaj.org/article/a6d04f43521d456299fa642bbb175599
Autor:
Jeong-Hun Yoo, Han-Gyeol Yeom, WooSang Shin, Jong Pil Yun, Jong Hyun Lee, Seung Hyun Jeong, Hun Jun Lim, Jun Lee, Bong Chul Kim
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Abstract This paper proposes a convolutional neural network (CNN)-based deep learning model for predicting the difficulty of extracting a mandibular third molar using a panoramic radiographic image. The applied dataset includes a total of 1053 mandib
Externí odkaz:
https://doaj.org/article/ca8290bdccde45128660e9a4deb20ddd
Publikováno v:
Scientific Reports, Vol 10, Iss 1, Pp 1-5 (2020)
Abstract Facial photographs of the subjects are often used in the diagnosis process of orthognathic surgery. The aim of this study was to determine whether convolutional neural networks (CNNs) can judge soft tissue profiles requiring orthognathic sur
Externí odkaz:
https://doaj.org/article/60ac178f95e64fcb865e207ee1f34a63
Publikováno v:
IEEE Transactions on Industrial Informatics. 19:6982-6992