References
H. Andrä, N. Combaret, J. Dvorkin, E. Glatt, J. Han, M. Kabel, Y. Keehm, F. Krzikalla, M. Lee, C. Madonna, M. Marsh, T. Mukerji, E. H. Saenger, R. Sain, N. Saxena, S. Ricker, A. Wiegmann, X. Zhan, Digital rock physics benchmarks – Part I: Imaging and segmentation, Computers & Geosciences (2013), https://doi.org/10.1016/j.cageo.2012.09.005
H. Andrä, N. Combaret, J. Dvorkin, E. Glatt, J. Han, M. Kabel, Y. Keehm, F. Krzikalla, M. Lee, C. Madonna, M. Marsh, T. Mukerji, E. H. Saenger, R. Sain, N. Saxena, S. Ricker, A. Wiegmann, X. Zhan, Digital rock physics benchmarks – Part II: Computing effective properties, Computers & Geosciences (2013), http://dx.doi.org/10.1016/j.cageo.2012.09.008
I. Arganda-Carreras, V. Kaynig, C. Rueden, K. W. Eliceiri, J. Schindelin, A. Cardona, H. S. Seung, Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification, Bioinformatics (2017), https://doi.org/10.1093/bioinformatics/btx180
V. Chandra, Ali I. Al-Naimi, Petroleum Engineering Research Center, King Abdullah University of Science and Technology
T. Chen, C. Guestrin, XGBoost A Scalable Boosting System, Machine Learning (2016), https://doi.org/10.48550/arXiv.1603.02754
H. Drucker, C. Cortes, Boosting Decision Trees, Advances in Neural Information (1995), https://www.researchgate.net/publication/221620492_Boosting_Decision_Trees
J. H. Fitschen, J. Ma, S. Schuff, Removal of curtaining effects by a variational model with directional forward differences, Computer Vision and Image Understanding (2017), https://doi.org/10.1016/j.cviu.2016.12.008
Github, XG Boost Tutorials, Introduction to Boosted Trees, https://xgboost.readthedocs.io/en/latest/tutorials/model.html
Github, XG Boost Python Package, Python API Reference, https://xgboost.readthedocs.io/en/latest/python/python_api.html
N. Phansalkar, S. More, A. Sabale, M. Joshi, Adaptive local thresholding for detection of nuclei in diversity stained cytology images, International Conference on Communications and Signal Processing (2011), https://doi.org/10.1109/ICCSP.2011.5739305
O. Ronneberger, P. Fischer, T. Brox, U-Net: Convolutional Networks for Biomedical Image Segmentation, Medical Image Computing and Computer-Assisted Intervention – MICCAI (2015), https://doi.org/10.1007/978-3-319-24574-4_28
J. Sauvola, M. Pietikäinen, Adaptive document image binarization, Pattern Recognition (2000), https://doi.org/10.1016/S0031-3203(99)00055-2
J. Sijbers, A. Postnov, Reduction of ring artefacts in high resolution micro-CT reconstructions, Physics in Medicine and Biology (2004), https://doi.org/10.1088/0031-9155/49/14/N06