140 REFERENCES Bellian, J. A., Kerans, C. and Jennette, D. C. (2005). Digital outcrop models: Applications of terrestrial scanning lidar technology in stratigraphic modeling. Journal of Sedimentary Research. 75(2), 166176. Bissig, T., Ullrich, T. D., Tosdal, R. M., Friedman, R. and Ebert, S. (2008). The time-space distribution of Eocene to Miocene magmatism in the central Peruvian polymetallic province and its metallogenetic implications. Journal of South American Earth Sciences. 26(1), 16-35. Bochkovskiy, A., Wang, C.-Y. and Liao, H.-Y. M. (2020). YOLOv4: Optimal Speed and Accuracy of Object Detection. arXiv preprint arXiv:2004.10934. Goodfellow, I., Bengio, Y. and Courville, A. (2016). Deep Learning. MIT Press, Cambridge, MA. He, K., Gkioxari, G., Dollar, P. and Girshick, R. (2017). Mask R-CNN. Proceedings of the IEEE International Conference on Computer Vision, 2961-2969. Krizhevsky, A., Sutskever, I. and Hinton, G. E. (2012). ImageNet classification with deep convolutional neural networks. Advances in Neural Information Processing Systems. 25, 1097-1105. Noble, D. C. and McKee, E. H. (1999). The Miocene metallogenic belt of central and northern Peru. In: Skinner, B. J. (ed.), Geology and Ore Deposits of the Central Andes. Society of Economic Geologists Special Publication 7, 155-193. Riquelme, A., Tomas, R., Cano, M., Pastor, J. L. and Abellan, A. (2018). Automatic Mapping of Discontinuity Persistence on Rock Masses Using 3D Point Clouds. Rock Mechanics and Rock Engineering. 51, 3005-3028. Ronneberger, O., Fischer, P. and Brox, T. (2015). U-Net: Convolutional Networks for Biomedical Image Segmentation. Medical Image Computing and Computer-Assisted Intervention, 234-241. Soler, P. and Bonhomme, M. G. (1988). Oligocene magmatic activity and associated mineralization in the polymetallic belt of central Peru. Economic Geology. 83, 657-663. Webster, T. L., Murphy, J. B., Gosse, J. C. and Spooner, I. (2006). The application of lidar-derived digital elevation model analysis to geological mapping: an example from the Fundy Basin, Nova Scotia, Canada. Canadian Journal of Remote Sensing. 32(3), 173-193. Windrim, L., Melkumyan, A., Murphy, R. J., Chlingaryan, A. and Leung, R. (2023). Unsupervised ore/waste classification on open-cut mine faces using close-range hyperspectral data. arXiv preprint arXiv:2302.04936.
RkJQdWJsaXNoZXIy MTM0Mzk2