| Deep dense and convolutional autoencoders for machine acoustic anomaly detection G Coelho, P Pereira, L Matos, A Ribeiro, EC Nunes, A Ferreira, P Cortez, ... Artificial Intelligence Applications and Innovations: 17th IFIP WG 12.5 …, 2021 | 40* | 2021 |
| Multi-objective grammatical evolution of decision trees for mobile marketing user conversion prediction PJ Pereira, P Cortez, R Mendes Expert Systems with Applications 168, 114287, 2021 | 34 | 2021 |
| Forecasting store foot traffic using facial recognition, time series and support vector machines P Cortez, LM Matos, PJ Pereira, N Santos, D Duque International Joint Conference SOCO’16-CISIS’16-ICEUTE’16: San Sebastián …, 2017 | 22 | 2017 |
| Multi-step time series prediction intervals using neuroevolution P Cortez, PJ Pereira, R Mendes Neural Computing and Applications, 1-15, 2020 | 19 | 2020 |
| Using deep autoencoders for in-vehicle audio anomaly detection PJ Pereira, G Coelho, A Ribeiro, LM Matos, EC Nunes, A Ferreira, ... Procedia Computer Science 192, 298-307, 2021 | 16 | 2021 |
| Deep autoencoders for acoustic anomaly detection: experiments with working machine and in-vehicle audio G Coelho, LM Matos, PJ Pereira, A Ferreira, A Pilastri, P Cortez Neural Computing and Applications 34 (22), 19485-19499, 2022 | 8 | 2022 |
| A categorical clustering of publishers for mobile performance marketing S Silva, P Cortez, R Mendes, PJ Pereira, LM Matos, L Garcia International Joint Conference SOCO’18-CISIS’18-ICEUTE’18: San Sebastián …, 2019 | 8 | 2019 |
| A comparison of machine learning methods for extremely unbalanced industrial quality data PJ Pereira, A Pereira, P Cortez, A Pilastri Progress in Artificial Intelligence: 20th EPIA Conference on Artificial …, 2021 | 6 | 2021 |
| Using neuroevolution for predicting mobile marketing conversion PJ Pereira, P Pinto, R Mendes, P Cortez, A Moreau Progress in Artificial Intelligence: 19th EPIA Conference on Artificial …, 2019 | 4 | 2019 |
| A comparison of automated time series forecasting tools for smart cities PJ Pereira, N Costa, M Barros, P Cortez, D Durães, A Silva, J Machado EPIA Conference on Artificial Intelligence, 551-562, 2022 | 3 | 2022 |
| AI4CITY-An automated machine learning platform for smart cities PJ Pereira, C Gonçalves, LL Nunes, P Cortez, A Pilastri Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 886-889, 2023 | 2 | 2023 |
| Multi-objective learning of neural network time series prediction intervals PJ Pereira, P Cortez, R Mendes Progress in Artificial Intelligence: 18th EPIA Conference on Artificial …, 2017 | 2 | 2017 |
| Predicting multiple domain queue waiting time via machine learning C Loureiro, PJ Pereira, P Cortez, P Guimarães, C Moreira, A Pinho International Conference on Computational Science and Its Applications, 404-421, 2023 | 1 | 2023 |
| An intelligent decision support system for production planning in garments industry R Ribeiro, A Pilastri, H Carvalho, A Matta, PJ Pereira, P Rocha, M Alves, ... International Conference on Intelligent Data Engineering and Automated …, 2021 | 1 | 2021 |
| A Comparison of Automated Machine Learning Tools for Predicting Energy Building Consumption in Smart Cities D Soares, PJ Pereira, P Cortez, C Gonçalves EPIA Conference on Artificial Intelligence, 311-322, 2023 | | 2023 |
| Modern Optimization of Predictive Models: An Application to Mobile Performance Marketing PJS Pereira PQDT-Global, 2021 | | 2021 |
Paulo CortezFull Professor, ALGORITMI, Department Information Systems, University of MinhoEmail confirmado em dsi.uminho.pt
