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The Transactions of
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Trans. Korean. Inst. Elect. Eng.
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2023-03
(Vol.72 No.03)
10.5370/KIEE.2023.72.3.440
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References
1
Yo-wei Chen, March 2020, Artificial intelligence in dentistry: current applications and future perspectives, QUINTESSENCE INTERNATIONAL, Vol. 51
2
Jun-Yong Hong, Sang Hyun Park, Young-Jin Jung, 2020, Artificial Intelligence Based Medical Imaging: An Overview, Journal of Radiological Science and Technology, Vol. 43, No. 3, pp. 195-208
3
https://www.denfoline.co.kr/news/articleView.html?idxno=21716
4
J. Long, E. Shelhamer, T. Darrell, 2015, Fully Convolutional Networks for Semantic Segmentation, The IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431-3440
5
O. Ronneberger, P. Fischer, and T. Brox, 2015, U-net: Convolutional networks for biomedical image segmentation, International Conference on Medical image computing and computer- assisted intervention
6
Z.W. Zhou, M.M.R. Siddiquee, N. Tajbakhsh, J.M. Liang, 2018, UNet++: A Nested U-Net Architecture for Medical Image Segmentation, Deep Learning in Medical Image Anylysis and Multimodal Learning for Clinical Decision Support, pp. 3-11
7
Huimin Huang, 2020, Unet 3+: A full-scale connected unet for medical image segmentation, 2020 IEEE International Conference on Acoustics, Vol. speech and signal processing(icassp)
8
Tsung-Yi Lin, Feb 2020, Focal loss for dense object detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 42, No. 2, pp. 318–327
9
F Pesapane, M Codari, F. Sardanelli, 2018, Artificial intelligence in medical imaging: Threat or opportunity? Radiologists again at the forefront of innovation in medicine, Eur Radiol Exp, Oct; vol.2, Vol. no.1, pp. 35
10
JC Trinder, Y Wang, A Sowmya, M. Palhang, Basel: Birkhäuser; 1997, Artificial intelligence in 3-D feature extraction, Automatic Extraction of Man-Made Objects from Aerial and Space Images. 2nd ed.
11
D Shen, G Wu, HI. Suk, 2017 Jun, Deep learning in medical image analysis, Annu Rev Biomed Eng. 19:221-48.
12
D RavR, C Wong, F Deligianni, M Berthelot, J Andreu-Perez, B Lo, 2017, Deep learning for health informatics, IEEE J Biomed Health Inform, Jan, Vol. 21, No. 1, pp. 4-21