JKSMI
Journal of the Korea Institute for
Structural Maintenance and Inspection
KSMI
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ISSN : 2234-6937 (Print)
ISSN : 2287-6979 (Online)
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Journal of the Korea Concrete Institute
J Korea Inst. Struct. Maint. Insp.
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Korea Citation Index (KCI)
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2019-12
(Vol.23 No.7)
10.11112/jksmi.2019.23.7.66
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References
1
I. Kazuya, I. Shinichiro, O. Kyosuke, M. Toshifumi, 2018, Object Detection in Ground-Penetrating Radar Images Using a Deep Convolutional Neural Network and Image Set Preparation by Migration, International Journal of Geophysics, Vol. 2018, No. , pp. 1-8
2
K. Morton, Recognizing subsurface target responses in ground penetrating radar data using convolutional neural networks, SPIE
3
J. Chae, H. Y. Ko, B. G. Lee, N. Kim, 2019, A Study on the Pipe Position Estimation in GPR Images Using Deep Learning Based Convolutional Neural Network, Journal of Internet Computing and Services, Vol. 20, No. 4, pp. 39-46
4
H. Y. Ko, N. Kim, 2019, Performance Analysis of Detecting buried pipelines in GPR images using Faster R-CNN, Journal of Convergence for information Technology, Vol. 9, No. 5, pp. 21-26
5
K. Venceslav, Sinisha P. , Dimitar T. , 2018, Detection and Classification of Land Mines from Ground Penetrating Radar Data Using Faster R-CNN, Published in 26th Telecommunications Forum, IEEE, Belgrade
6
C. Windsor, L. Capineri, P. Falorni, S. Matucci, G. Borgioli, 2005, The estimation of buried pipe diameters using ground penetrating radar, Journal of Insight, Vol. 47, No. 7, pp. 394-399
7
S. Shihab, W. AI-Nuaimy, 2005, Radius Estimation for Cylindrical Objects Detected by Ground Penetrating Radar, Journal of Subsurface Sensing Technologies and Applications, Vol. 6, No. 2, pp. 151-166
8
S. W. Park, D. Y. Kim, 2018, Comparision of Image Classification Performance by Activation Functions in Convolutional Neural Networks, Journal of Korea Multimedia Society, Vol. 21, No. 10, pp. 1142-1149
9
J. Bae, J. Kim, 2019, Deep Learning Music genre automatic classification voting system using Softmax, Journal of the Korea Institute of Information and Communication Engineering, Vol. 23, No. 1, pp. 27-32
10
J. Y. Rhee, H. S. Kim, J. J. Choi, 2017, Deterioration Characteristics of Concrete Bridge Decks and Advances in Condition Assessment with Air-coupled GPR, Journal of the Korea Concrete Institute, Vol. 29, No. 2, pp. 737-738
11
H. H. Lee, 2016, Image Processing of GPR Detection Data, Journal of the Korea Institute for Structural Maintenance and Inspection, Vol. 20, No. 4, pp. 104-110
12
H. W. Ahn, 2009, Underground Buried GPR Exploration Study for Subway Construction, Inha University, Master degree paper