| The effect of batch size on the generalizability of the convolutional neural networks on a histopathology dataset I Kandel, M Castelli ICT express 6 (4), 312-315, 2020 | 731 | 2020 |
| The impact of big data analytics on firms’ high value business performance A Popovič, R Hackney, R Tassabehji, M Castelli Information Systems Frontiers 20 (2), 209-222, 2018 | 584 | 2018 |
| Structural similarity index (SSIM) revisited: A data-driven approach I Bakurov, M Buzzelli, R Schettini, M Castelli, L Vanneschi Expert Systems with Applications 189, 116087, 2022 | 405 | 2022 |
| A machine learning approach to predict air quality in California M Castelli, FM Clemente, A Popovič, S Silva, L Vanneschi Complexity 2020 (1), 8049504, 2020 | 361 | 2020 |
| Genetic programming needs better benchmarks J McDermott, DR White, S Luke, L Manzoni, M Castelli, L Vanneschi, ... Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012 | 345 | 2012 |
| Better GP benchmarks: community survey results and proposals DR White, J McDermott, M Castelli, L Manzoni, BW Goldman, ... Genetic programming and evolvable machines 14 (1), 3-29, 2013 | 299 | 2013 |
| Transfer learning with convolutional neural networks for diabetic retinopathy image classification. A review I Kandel, M Castelli Applied Sciences 10 (6), 2021, 2020 | 249 | 2020 |
| A survey of semantic methods in genetic programming L Vanneschi, M Castelli, S Silva Genetic Programming and Evolvable Machines 15 (2), 195-214, 2014 | 247 | 2014 |
| Prediction of high performance concrete strength using genetic programming with geometric semantic genetic operators M Castelli, L Vanneschi, S Silva Expert Systems with Applications 40 (17), 6856-6862, 2013 | 195 | 2013 |
| Combinatorial optimization problems and metaheuristics: Review, challenges, design, and development F Peres, M Castelli Applied sciences 11 (14), 6449, 2021 | 191 | 2021 |
| Measuring bloat, overfitting and functional complexity in genetic programming L Vanneschi, M Castelli, S Silva Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010 | 187 | 2010 |
| Prediction of energy performance of residential buildings: A genetic programming approach M Castelli, L Trujillo, L Vanneschi, A Popovič Energy and Buildings 102, 67-74, 2015 | 168 | 2015 |
| Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country F Cruz-Jesus, M Castelli, T Oliveira, R Mendes, C Nunes, M Sa-Velho, ... Heliyon 6 (6), 2020 | 163 | 2020 |
| A C++ framework for geometric semantic genetic programming M Castelli, S Silva, L Vanneschi Genetic Programming and Evolvable Machines 16 (1), 73-81, 2015 | 155 | 2015 |
| A new implementation of geometric semantic GP and its application to problems in pharmacokinetics L Vanneschi, M Castelli, L Manzoni, S Silva European Conference on Genetic Programming, 205-216, 2013 | 151 | 2013 |
| Brain tumor diagnosis using machine learning, convolutional neural networks, capsule neural networks and vision transformers, applied to MRI: a survey AA Akinyelu, F Zaccagna, JT Grist, M Castelli, L Rundo Journal of imaging 8 (8), 205, 2022 | 148 | 2022 |
| An artificial intelligence system for predicting customer default in e-commerce L Vanneschi, DM Horn, M Castelli, A Popovič Expert Systems with Applications 104, 1-21, 2018 | 138 | 2018 |
| Geometric semantic genetic programming for real life applications L Vanneschi, S Silva, M Castelli, L Manzoni Genetic programming theory and practice xi, 191-209, 2014 | 130 | 2014 |
| Comparative study of first order optimizers for image classification using convolutional neural networks on histopathology images I Kandel, M Castelli, A Popovič Journal of imaging 6 (9), 92, 2020 | 124 | 2020 |
| Predicting burned areas of forest fires: an artificial intelligence approach M Castelli, L Vanneschi, A Popovič Fire ecology 11 (1), 106-118, 2015 | 121 | 2015 |
Leonardo VanneschiNOVA IMS, Universidade Nova de LisboaVerified email at isegi.unl.pt
