A Study on the Pipe Position Estimation in GPR Images Using Deep Learning Based Convolutional Neural Network
Jihun Chae, Hyoung-yong Ko, Byoung-gil Lee, Namgi Kim, Journal of Internet Computing and Services, Vol. 20, No. 4, pp. 39-46, Aug. 2019
10.7472/jksii.2019.20.4.39, Full Text:
Keywords: sink holes, pipe, GPR, Image recognition, underground detection, CNN, deep-learning
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Cite this article
[APA Style]
Chae, J., Ko, H., Lee, B., & Kim, N. (2019). A Study on the Pipe Position Estimation in GPR Images Using Deep Learning Based Convolutional Neural Network. Journal of Internet Computing and Services, 20(4), 39-46. DOI: 10.7472/jksii.2019.20.4.39.
[IEEE Style]
J. Chae, H. Ko, B. Lee, N. Kim, "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, 2019. DOI: 10.7472/jksii.2019.20.4.39.
[ACM Style]
Jihun Chae, Hyoung-yong Ko, Byoung-gil Lee, and Namgi 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, 20, 4, (2019), 39-46. DOI: 10.7472/jksii.2019.20.4.39.