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Journal of the Korean Society of Civil Engineers

Journal of the Korean Society of Civil Engineers

ISO Journal TitleKSCE J. Civ. Environ. Eng. Res.
  • Open Access, Bi-monthly

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  3. 2018-12 (v.38 n.6)
  4. 10.12652/Ksce.2018.38.6.0859
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1 
Bandeira, L., Ding, W. and Stepinski, T. F. (2012). "Detection of subkilometer craters in high resolution planetary images using shape and texture features." Advances in Space Research, Vol. 49, pp. 64-74.DOI
2 
Chen, M., Liu, D., Qian, K., Li, J., Lei, M. and Zhou, Y. (2018). "Lunar crater detection based on terrain analysis and mathematical morphology methods using digital elevation models." IEEE Transactions on Geoscience and Remote Sensing, Vol. 56, No. 7, pp. 3681-3692.DOI
3 
Cohen, J. P., Lo, H. Z., Lu, T. and Ding, W. (2016). "Crater detection via convolutional neural networks." Proc. of 47th Lunar and Planetary Science Conference, Houston, U.S.A., p. 1143.
4 
Emami, E., Bebis, G., Nefian, A. and Fong, T. (2015). "Automatic crater detection using convex grouping and convolutional neural networks." Proc. of International Symposium on Visual Computing, Springer, Cham, pp. 213-224.DOI
5 
Girshick, R. (2015). "Fast R-CNN." Proc. of the IEEE International Conference on Computer Vision, Las Condes, Chile, pp. 1440-1448.DOI
6 
Hong, S., Kim, Y., Seo, M. and Shin, H. (2018) "Geographic distribution analysis of lunar in-situ resource and topography to construct lunar base." Journal of the Korea Academia-Industrial Cooperation Society, Vol. 19, pp. 669-676 (in Korean).
7 
Kim, K. J. (2017). "A research trend on lunar resource and lunar base." The Journal of The Petrological Society of Korea, Vol. 26, No. 4, pp. 373-384 (In Korean).
8 
Palafox, L. F., Hamilton, C. W., Scheidt, S. P. and Alvarez, A. M. (2017). "Automated detection of geological landforms on mars using convolutional neural networks." Computers & Geosciences, Vol. 101, pp. 48-56.DOI
9 
Ren, S., He, K., Girshick, R. and Sun, J. (2015), "Faster R-CNN: towards real-time object detection with region proposal networks." Advances in neural information processing systems, pp. 91-99.
10 
Robbins, S. J., Antonenko, I., Kirchoff, M. R., Chapman, C. R., Fassett, C. I., Herrick, R. R., Singer, K., Zanetti, M., Lehan, C., Huang, D. and Gay, P. L. (2014). "The variability of crater identification among expert and community crater analysts." Icarus 234, pp. 109-131.DOI
11 
Salamuniccar, G. and Loncaric, S. (2010). "Method for crater detection from digital topography data: interpolation based improvement and application to Lunar SELENE LALT data." Proc. of 38th COSPAR Scientific Assembly, Vol. 38, p. 3.
12 
Silburt, A., Ali-Dib, .M, Zhu, C., Jackson, A., Menou, K. (2018) DeepMoon Supplemental Materials. Available at https://zenodo.org/ record/1133969#.W_47ODMUmHs (Accessed: March 23, 2018)
13 
Stepinski, T., Ding, W. and Vilalta, R. (2012). "Detecting impact craters in planetary images using machine learning." Intelligent data analysis for real-life applications: theory and practice, IGI Global, pp. 146-159DOI
14 
Wetzler, P., Honda, R., Enke, B., Merline, W., Chapman, C. and Burl, M. (2005). "Learning to detect small impact craters." Proc. of 7th IEEE Workshop on Application of Computer Vision, Vol. 1. pp. 178-184.DOI
15 
Zhu, M. (2004), "Recall, precision and average precision." Department of Statistics and Actuarial Science, University of Waterloo, Vol. 2, p. 30.
16 
NASA (2018). Lunar Reconnaissance Orbiter., Available at: https://lunar.gsfc.nasa.gov (Accessed: October 12, 2018)