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2021 Vol.31, Issue 5 Preview Page

Original Article

October 2021. pp. 374-384
Abstract
References
1
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G., Isard, M., Jia, Y., Jozefowicz, R., Kaiser, L., Kudlur, M., Levenberg, J., Mané, D., Monga, R., Moore, S., Murray, D., Olah, C., Schuster, M., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Viégas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., & Zheng, X. (2015), “TensorFlow: Large-scale machine learning on heterogeneous systems”, Software available from http://tensorflow.org/.
2
Andrä, H., Combaret, N., Dvorkin, J., Glatt, E., Han, J., Kabel, M., Keehm, Y., Krzikalla, F., Lee M., and Madonna, C. (2013), “Digital rock physics benchmarks-Part I: Imaging and segmentation”, Comput. Geosci. 50, pp. 25-32. 10.1016/j.cageo.2012.09.005
3
Crandall D, Moore J, Gill M, Stadelman M. (2017), “CT scanning and flow measurements of shale fractures after multiple shearing events”, Int J Rock Mech Min Sci. 100, pp.177-187. 10.1016/j.ijrmms.2017.10.016
4
Girshick, R. (2015), Fast R-CNN. In: ICCV. 10.1109/ICCV.2015.169
5
He, K., Gkioxari, G., Dollár, P., Girshick, R. B. (2017), “Mask R-CNN”, CoRR abs/1703.06870 (2017). arXiv:1703.06870 http://arxiv.org/abs/1703.06870 10.1109/ICCV.2017.322
6
He, K., Zhang, X., Ren, S., and Sun, J. (2015), “Delving deep into rectifiers: Surpassing human-level performance on ImageNet classification”, In: Proceedings of the IEEE international conference on computer vision, IEEE, NY, USA, pp. 1026-1034. 10.1109/ICCV.2015.123
7
Ketcham, R. A., and Carlson, W. D. (2001), “Acquisition, optimization and interpretation of X-ray computed tomographic imagery: applications to the geosciences”, Comput. Geosci. Geosc. 27, pp. 381-400. 10.1016/S0098-3004(00)00116-3
8
Kling, T., Huo, D., Schwarz, J.O., Enzmann, F., Benson, S., Blum, P. (2016), “Simulating stress-dependent fluid flow in a fracturedcore sample using real-time X-ray CT data”, Solid Earth, 7, pp. 1109-1124. 10.5194/se-7-1109-2016
9
Kyle, J. R., and Ketcham, R. A. (2015), “Application of high resolution X-ray computed tomography to mineral deposit origin, evaluation, and processing”, Ore Geol. Rev. 65, pp. 821-839. 10.1016/j.oregeorev.2014.09.034
10
Lin, T., Dollár, P., Girshick, R.B., He, K., Hariharan, B., Belongie, S. J. (2017), “Feature pyramid networks for object detection”, CVPR. 10.1109/CVPR.2017.106PMC5744014
11
Lin, T., Maire, M., Belongie, S. J., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick C. L. (2014), “Microsoft COCO: common objects in context”, in Computer Vision - ECCV 2014 - 13th European Conference, Zurich,Switzerland, September 6-12, 2014, Proceedings, Part V, ser. LectureNotes in Computer Science, vol. 8693. Springer, pp. 740-755. 10.1007/978-3-319-10602-1_48
12
Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu C-Y. (2016), “SSD: Single Shot MultiBox Detector”, ArXiv151202325 Cs. 2016; 9905:21-37. 10.1007/978-3-319-46448-0_2
13
Otsu, N., 1979. A threshold selection method from gray-level histograms. IEEE Trans. Sys. Man. Cyber. 9 (1), 62-66. doi:10.1109/TSMC.1979.4310076. 10.1109/TSMC.1979.4310076
14
Redmon, J., Divvala, S., Girshick, R., Farhadi, A. (2016), “You only look once: Unified, real-time object detection”, in IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 10.1109/CVPR.2016.91
15
Ren, S., He, K., Girshick, R., Sun, J. (2015), “Faster R-CNN: Towards real-time object detection with region proposal networks”, in: NIPS.
16
Ronneberger, P. Fischer, Brox, T. (2015), “U-Net: Convolutional Networks for Biomedical Image Segmentation”, MICCAI, Springer, LNCS, 9351, pp. 234-241. 10.1007/978-3-319-24574-4_28
17
Schmitt, M., Halisch, M., Müller, C., and Fernandes, C. P. (2016), “Classification and quantification of pore shapes in sandstone reservoir rocks with 3-D X-ray microcomputed tomography”, Solid Earth. 7, pp. 285-300. 10.5194/se-7-285-2016
18
Voorn, M., Exner, U., and Rath, A. (2013), “Multiscale Hessian fracture filtering for the enhancement and segmentation of narrow fractures in 3D image data”, Comput. Geosci. 57, pp. 44-53. 10.1016/j.cageo.2013.03.006
19
Vu, T. X., Jang, H., Pham, T. X., and Yoo, C. D. (2019), “Cascade RPN: Delving into high-quality region proposal network with adaptive convolution”, in Proc. NIPS, pp. 1-11.
20
Wennberg, O. P., Rennan, L., and Basquet, R. (2009), “Computed tomography scan imaging of natural open fractures in a porous rock; geometry and fluid flow”, Geophys. Prospect. 57, pp. 239-249. 10.1111/j.1365-2478.2009.00784.x
21
Yen, J.Y., 1970. An algorithm for finding shortest routes from all source nodes to a given destination in general networks. Quarterly of Applied Mathematics. 27 (4), 526-530. doi:10.1090/qam/253822. 10.1090/qam/253822
Information
  • Publisher :Korean Society for Rock Mechanics and Rock Engineering
  • Publisher(Ko) :한국암반공학회
  • Journal Title :Tunnel and Underground Space
  • Journal Title(Ko) :터널과 지하공간
  • Volume : 31
  • No :5
  • Pages :374-384
  • Received Date :2021. 09. 14
  • Revised Date :2021. 10. 13
  • Accepted Date : 2021. 10. 18