| Convolutional neural network for remote-sensing scene classification: Transfer learning analysis R Pires de Lima, K Marfurt Remote Sensing 12 (1), 86, 2019 | 258 | 2019 |
| Deep convolutional neural networks as a geological image classification tool RP de Lima, A Bonar, DD Coronado, K Marfurt, C Nicholson The Sedimentary Record 17 (2), 4-9, 2019 | 70 | 2019 |
| Convolutional neural networks as aid in core lithofacies classification R Pires de Lima, F Suriamin, KJ Marfurt, MJ Pranter Interpretation 7 (3), 1-50, 2019 | 68 | 2019 |
| Petrographic microfacies classification with deep convolutional neural networks RP de Lima, D Duarte, C Nicholson, R Slatt, KJ Marfurt Computers & Geosciences 142, 104481, 2020 | 58 | 2020 |
| Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms R Pires de Lima, Y Chen, Y Lin Space Weather 18 (2), e2019SW002399, 2020 | 34 | 2020 |
| Normal or abnormal? Machine learning for the leakage detection in carbon sequestration projects using pressure field data S Sinha, RP de Lima, Y Lin, AY Sun, N Symons, R Pawar, G Guthrie International Journal of Greenhouse Gas Control 103, 103189, 2020 | 29 | 2020 |
| Convolutional neural networks as an aid to biostratigraphy and micropaleontology: a test on Late Paleozoic microfossils R PIRES DE LIMA, KF Welch, JE Barrick, KJ Marfurt, R Burkhalter, ... Palaios 35 (9), 391-402, 2020 | 27 | 2020 |
| Principal component analysis and K-means analysis of airborne gamma-ray spectrometry surveys RP de Lima, KJ Marfurt SEG Technical Program Expanded Abstracts 2018, 2277-2281, 2018 | 25 | 2018 |
| Pretraining Convolutional Neural Networks for Mudstone Petrographic Thin-Section Image Classification R Pires de Lima, D Duarte Geosciences 11 (8), 336, 2021 | 18 | 2021 |
| Progress and Challenges in Deep Learning Analysis of Geoscience Images RP De Lima, K Marfurt, D Duarte, A Bonar 81st EAGE Conference and Exhibition 2019 2019 (1), 1-5, 2019 | 17 | 2019 |
| Deep convolutional neural networks as an estimator of porosity in thin-section images for unconventional reservoirs D Duarte-Coronado, J Tellez-Rodriguez, R Pires de Lima, K Marfurt, ... SEG Technical Program Expanded Abstracts 2019, 3181-3184, 2019 | 11 | 2019 |
| Statistical controls on induced seismicity S Sinha, Y Wen, R Pires De Lima, K Marfurt Unconventional Resources Technology Conference, Houston, Texas, 23-25 July …, 2018 | 10 | 2018 |
| Lithofacies identification in cores using deep learning segmentation and the role of geoscientists: Turbidite deposits (Gulf of Mexico and North Sea) O Falivene, NC Auchter, RP de Lima, L Kleipool, JG Solum, P Zarian, ... AAPG Bulletin 106 (7), 1357-1372, 2022 | 9 | 2022 |
| Transforming seismic data into pseudo-RGB images to predict CO2 leakage using pre-learned convolutional neural networks weights R Pires de Lima, Y Lin, KJ Marfurt SEG Technical Program Expanded Abstracts 2019, 2368-2372, 2019 | 8 | 2019 |
| Geophysical data integration and machine learning for multi-target leakage estimation in geologic carbon sequestration RP de Lima, Y Lin SEG Technical Program Expanded Abstracts 2019, 2333-2337, 2019 | 8 | 2019 |
| Seismic Inversion Based SRV and Reserves Estimation for Shale Plays S Sinha, KJ Marfurt, D Devegowda, R Pires de Lima, S Verma SPE Annual Technical Conference and Exhibition, 2017 | 6 | 2017 |
| Generating a labeled data set to train machine learning algorithms for lithologic classification of drill cuttings D Becerra, R Pires de Lima, H Galvis-Portilla, CR Clarkson Interpretation 10 (3), SE85-SE100, 2022 | 5 | 2022 |
| PreMevE Update: Forecasting Ultra-relativistic Electrons inside Earth's Outer Radiation Belt S Sinha, Y Chen, Y Lin, R Pires de Lima Space Weather 19 (9), e2021SW002773, 2021 | 5 | 2021 |
| Comparison of clustering techniques to define chemofacies in mississippian rocks in the STACK Play, Oklahoma D Duarte, R Lima, R Slatt, K Marfurt American association of petroleum geologists search and discovery 42523, 2020 | 5 | 2020 |
| Quantifying uncertainty in unsupervised machine learning methods for seismic facies using outcrop-derived 3D models and synthetic seismic data K La Marca, H Bedle, L Stright, R Pires de Lima, KJ Marfurt Second International Meeting for Applied Geoscience & Energy, 1312-1316, 2022 | 3 | 2022 |
Youzuo LinAssociate Professor at The University of North Carolina at Chapel HillVerified email at unc.edu
