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Convolutional Neural Networks and Image Patches for Lithological Classification of Brazilian Pre-Salt Rocks.

, , , , , , , and . VISIGRAPP (3): VISAPP, page 648-655. SCITEPRESS, (2024)

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Corrigendum to 'Segmentation of sandstone thin section images with separation of touching grains using optimum path forest operators' Computers & Geosciences (2013) 146-157., , , and . Comput. Geosci., (2014)Characterization of fracture geometry with computed microtomography rock images., , , and . GEOINFO, page 111-122. MCTIC/INPE, (2022)Segmentation of sandstone thin section images with separation of touching grains using optimum path forest operators., , , and . Comput. Geosci., (2013)Learning to Classify Seismic Images with Deep Optimum-Path Forest., , , , and . SIBGRAPI, page 401-407. IEEE Computer Society, (2016)3D porosity prediction from seismic inversion and neural networks., and . Comput. Geosci., 37 (8): 1174-1180 (2011)A Combined Noisy Borehole Image Log Segmentation Method., , and . IWSSIP, page 1-5. IEEE, (2023)Transformer Model for Fault Detection from Brazilian Pre-salt Seismic Data., , , , and . BRACIS (2), volume 14196 of Lecture Notes in Computer Science, page 3-17. Springer, (2023)A fast approach for unsupervised karst feature identification using GPU., , , , and . Comput. Geosci., (2018)Convolutional Neural Networks and Image Patches for Lithological Classification of Brazilian Pre-Salt Rocks., , , , , , , and . VISIGRAPP (3): VISAPP, page 648-655. SCITEPRESS, (2024)