| Explainable artificial intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible ai A Barredo Arrieta, N Díaz-Rodríguez, J Del Ser, A Bennetot, S Tabik, ... Information Fusion 58, 82-115, 2020 | 7123 | 2020 |
| Deep learning in video multi-object tracking: A survey G Ciaparrone, FL Sánchez, S Tabik, L Troiano, R Tagliaferri, F Herrera Neurocomputing 381, 61-88, 2020 | 668 | 2020 |
| COVIDGR dataset and COVID-SDNet methodology for predicting COVID-19 based on Chest X-Ray images S Tabik, A Gómez-Ríos, JL Martín-Rodríguez, I Sevillano-García, ... IEEE Journal of Biomedical and Health Informatics 26 (12), 3595 - 3605, 2020 | 385 | 2020 |
| Automatic Handgun Detection Alarm in Videos Using Deep Learning R Olmos, S Tabik, F Herrera Neurocomputing 275, 66-72, 2018 | 260 | 2018 |
| Deep-learning versus OBIA for scattered shrub detection with Google Earth imagery: Ziziphus lotus as case study E Guirado, S Tabik, D Alcaraz-Segura, J Cabello, F Herrera Remote Sensing 9 (12), 2017 | 206* | 2017 |
| Detection of Fir Trees (Abies sibirica) Damaged by the Bark Beetle in Unmanned Aerial Vehicle Images with Deep Learning A Safonova, S Tabik, D Alcaraz-Segura, A Rubtsov, Y Maglinets, ... Remote sensing 11 (6), 643, 2019 | 169 | 2019 |
| Object detection binary classifiers methodology based on deep learning to identify small objects handled similarly: Application in video surveillance F Pérez-Hernández, S Tabik, A Lamas, R Olmos, H Fujita, F Herrera Knowledge-Based Systems 194, 105590, 2020 | 162 | 2020 |
| Towards Highly Accurate Coral Texture Images Classification Using Deep Convolutional Neural Networks and Data Augmentation A Gómez-Ríos, S Tabik, J Luengo, ASM Shihavuddin, B Krawczyk, ... Expert Systems with Applications 118, 315-328, 2019 | 149 | 2019 |
| BreakHis based breast cancer automatic diagnosis using deep learning: Taxonomy, survey and insights Y Benhammou, B Achchab, F Herrera, S Tabik Neurocomputing 375, 9-24, 2020 | 147 | 2020 |
| Whale counting in satellite and aerial images with deep learning E Guirado, S Tabik, ML Rivas, D Alcaraz-Segura, F Herrera Scientific reports 9 (1), 14259, 2019 | 133 | 2019 |
| Analytical modeling of pipeline parallelism A Navarro, R Asenjo, S Tabik, C Cascaval 2009 18th international conference on parallel architectures and compilation …, 2009 | 121 | 2009 |
| Evaluating the consistency of the 1982–1999 NDVI trends in the Iberian Peninsula across four time-series derived from the AVHRR sensor: LTDR, GIMMS, FASIR, and PAL-II D Alcaraz-Segura, E Liras, S Tabik, J Paruelo, J Cabello Sensors 10 (2), 1291-1314, 2010 | 107 | 2010 |
| Brightness guided preprocessing for automatic cold steel weapon detection in surveillance videos with deep learning A Castillo, S Tabik, F Pérez, R Olmos, F Herrera Neurocomputing 330, 151-161, 2019 | 103 | 2019 |
| A snapshot of image pre-processing for convolutional neural networks: case study of MNIST S Tabik, D Peralta, A Herrera-Poyatos, F Herrera International Journal of Computational Intelligence Systems 10, 555–568, 2017 | 97 | 2017 |
| Revisiting crowd behaviour analysis through deep learning: Taxonomy, anomaly detection, crowd emotions, datasets, opportunities and prospects FL Sánchez, I Hupont, S Tabik, F Herrera Information Fusion 64, 318-335, 2020 | 84 | 2020 |
| Simultaneous computation of total viewshed on large high resolution grids S Tabik, EL Zapata, LF Romero International Journal of Geographical Information Science 27 (4), 804-814, 2013 | 81 | 2013 |
| Deep learning in omics data analysis and precision medicine J Martorell-Marugán, S Tabik, Y Benhammou, C del Val, I Zwir, F Herrera, ... Exon Publications, 37-53, 2019 | 80 | 2019 |
| EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: The MonuMAI cultural heritage use case FH Natalia Díaz-Rodríguez, Alberto Lamas, Jules Sanchez, Gianni Franchi ... Information Fusion 79, 58-83, 2022 | 78 | 2022 |
| Olive tree biovolume from UAV multi-resolution image segmentation with mask R-CNN A Safonova, E Guirado, Y Maglinets, D Alcaraz-Segura, S Tabik Sensors 21 (5), 1617, 2021 | 75 | 2021 |
| A first study exploring the performance of the state-of-the art CNN model in the problem of breast cancer Y Benhammou, S Tabik, B Achchab, F Herrera Proceedings of the International Conference on Learning and Optimization …, 2018 | 57 | 2018 |
Francisco HerreraProfessor Computer Science and AI, DaSCI Research Institute, Granada University, Spain在 decsai.ugr.es 的电子邮件经过验证
