Koeshidayatullah, A., Morsilli, M., Lehrmann, D., Al-Ramadan, K., & Payne, J. (2020). Fully automated carbonate petrography using deep convolutional neural networks. Marine and Petroleum Geology, 122, 104687. Liu, H., Ren, Y.-L., Li, X., Hu, Y.-X., Wu, J.-P., Li, B., . . . Fang, W.-K. (2022). Rock thin-section analysis and identification based on artificial intelligent technique. Petroleum Science, 19(4), 1605-1621. Paucar, S., Mejía, C., & Collaguazo, V. (2025). Descripción automática de secciones delgadas de rocas: una aplicación Web. Aritficial Intelligence in Geosciences. Sitar, M., & Leary, R. (2023). colab_zirc_dims: a Google Colab-compatible toolset for automated and semi-automated measurement of mineral grains in laser ablation-inductively coupled plasma-mass spectrometry images using deep learning models. Geochronology, 5(1), 109126. Streckeisen, A. (1976). To each plutonic rock its proper name. Earth-science reviews, 12(1), 1-33. Sun, Z., Sandoval, L., Crystal-Ornelas, R., Mousavi, S., Wang, J., Lin, C., . . . others. (2022). A review of earth artificial intelligence. Computers & Geosciences, 159, 105034. Tatar, A., Haghighi, M., & Zeinijahromi, A. (2025). Experiments on image data augmentation techniques for geological rock type classification with convolutional neural networks. Journal of Rock Mechanics and Geotechnical Engineering, 17(1), 106-125. The Open University. (n.d.). How virtual thin sections are created. Retrieved 02 05, 2025, from The Open University: https://www.virtualmicroscope.org/about/how-a-thin-section-iscreated Thompson, S., Fueten, F., & Bockus, D. (2001). Mineral identification using artificial neural networks and the rotating polarizer stage. Computers & Geosciences, 27(9), 1081-1089. Tyagi, V. (2018). Understanding Digital Image Processing. CRC Press. van der Walt, S., Schönberger, J., Nunez, J., Boulogne, F., Warner, J., Yager, N., . . . contributors, t. s.-i. (2014, 06). scikit-image: image processing in Python. PeerJ, 2, e453. doi:10.7717/peerj.453 Vasilev, I. (2019). Advanced Deep Learning with Python: Design and implement advanced nextgeneration AI solutions using TensorFlow and PyTorch. Packt Publishing Ltd. Whitney, D., & Evans, B. (2010). Abbreviations for names of rock-forming minerals. American mineralogist, 95(1), 185-187. Wittchen, G., Truong, D., & Crawford, B. (2020). How Datarock is using PyTorch for more intelligent mining decision making. Retrieved 21 03, 2024, from Medium: https://medium.com Zaki, M., Sharma, S., Gurjar, S., Goyal, R., Jayadeva, & Krishnan, N. (2023). Cementron: Machine learning the alite and belite phases in cement clinker from optical images. Construction and Building Materials, 397, 132425.
RkJQdWJsaXNoZXIy MTM0Mzk2