| An efficient parametric algorithm for octree traversal J Revelles, C Urena, M Lastra Václav Skala-UNION Agency, 2000 | 173 | 2000 |
| A high performance fingerprint matching system for large databases based on GPU PD Gutierrez, M Lastra, F Herrera, JM Benítez IEEE Transactions on Information Forensics and Security 9 (1), 62-71, 2013 | 82 | 2013 |
| Simulation of shallow-water systems using graphics processing units M Lastra, JM Mantas, C Ureña, MJ Castro, JA García-Rodríguez Mathematics and Computers in Simulation 80 (3), 598-618, 2009 | 68 | 2009 |
| A high performance memetic algorithm for extremely high-dimensional problems M Lastra, D Molina, JM Benítez Information Sciences 293, 35-58, 2015 | 39 | 2015 |
| GPU-SME-kNN: Scalable and memory efficient kNN and lazy learning using GPUs PD Gutiérrez, M Lastra, J Bacardit, JM Benítez, F Herrera Information Sciences 373, 165-182, 2016 | 38 | 2016 |
| Fast fingerprint identification using GPUs M Lastra, J Carabaño, PD Gutiérrez, JM Benítez, F Herrera Information Sciences 301, 195-214, 2015 | 37 | 2015 |
| A particle-path based method for Monte-Carlo density estimation M Lastra, C Urena, J Revelles, R Montes Poster at: 13th EUROGRAPHICS Workshop on Rendering, 2002 | 34 | 2002 |
| SMOTE-GPU: Big data preprocessing on commodity hardware for imbalanced classification PD Gutiérrez, M Lastra, JM Benítez, F Herrera Progress in Artificial Intelligence 6, 347-354, 2017 | 32 | 2017 |
| Efficient multilayer shallow-water simulation system based on gpus M Lastra, MJC Díaz, C Ureña, M de la Asunción Mathematics and Computers in Simulation 148, 48-65, 2018 | 10 | 2018 |
| GENERIC BRDF SAMPLING-A Sampling Method for Global Illumination R Montes, C Urena, R García, M Lastra International Conference on Computer Graphics Theory and Applications 2, 191-198, 2008 | 6 | 2008 |
| A density estimation technique for radiosity M Lastra, C Ureña, J Revelles, R Montes In Ibero-American Symposium in Computer Graphics (SIACG’2002, 2002 | 6* | 2002 |
| A formal framework approach for ray-scene intersection test improvement J Revelles, M Lastra, R Montes, P Cano UNION Agency, 2003 | 5 | 2003 |
| Optimizing dense feed-forward neural networks L Balderas, M Lastra, JM Benítez Neural Networks 171, 229-241, 2024 | 4 | 2024 |
| Density estimation optimizations for global illumination R Garcia, C Urena, J Revelles, M Lastra, R Montes Václav Skala-UNION Agency, 2006 | 3 | 2006 |
| COVID-ViT: COVID-19 Detection Method Based on Vision Transformers L Balderas, M Lastra, AJ Láinez-Ramos-Bossini, JM Benítez International Conference on Intelligent Systems Design and Applications, 81-90, 2022 | 2 | 2022 |
| Optimizing Convolutional Neural Network Architectures L Balderas, M Lastra, JM Benítez Mathematics 12 (19), 3032, 2024 | 1 | 2024 |
| GPU Processing for Biometric Big Data Based Identification. Why and what for? M Lastra, PD Gutiérrez, JM Benítez, F Herrera Biostatistics and Biometrics Open Access Journal 2 (1), 2017 | 1 | 2017 |
| An Importance Sampling Method for Arbitrary BRDFs R Montes, C Urena, R García, M Lastra Computer Vision and Computer Graphics. Theory and Applications …, 2009 | 1 | 2009 |
| Un Algoritmo de Muestreo exacto para BRDFs Arbitrarias. R Montes, C Ureña, M Lastra, RJ García CEIG, 199-208, 2008 | 1 | 2008 |
| Interactive global illumination for quasi-static scenes RJ Garcia, C Urena, M Lastra, R Montes, J Revelles Proceedings Computer Graphics International, 2004., 128-131, 2004 | 1 | 2004 |
Carlos Ureña AlmagroUniversidad de GranadaVerified email at ugr.es
