Lus Miguel Matos
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
13
Venues
6
Active years
2019–2026
Best venue rank
C
Where they publish
Papers
13 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ICCSA | A Multivariate Multi-step Deep Learning Framework for InSAR Displacement Prediction. | Maria Maia, Lus Miguel Matos, Lus Magalhes, Joaquim Tinoco, Steffan Davies |
| 2026 | IDA | An End-to-End Framework for Measuring Product Cannibalization Using Multivariate Time Series Forecasting. | Daniela Martins, Lus Miguel Matos |
| 2024 | KES | Ahead of Time Prediction of Decorated Particleboard Production Disruptions and Defects Using Single and Multi-Target AutoML. | Arthur Matta, Lus Miguel Matos, Andr Luiz Pilastri, Jorge Miguel Silva, Miguel Bastos Gomes, Paulo Cortez |
| 2022 | ICAART | A Machine Learning Approach for Spare Parts Lifetime Estimation. | Lusa Macedo, Lus Miguel Matos, Paulo Cortez, Andr Domingues, Guilherme Moreira, Andr Luiz Pilastri |
| 2022 | IJCNN | A Deep Learning Approach to Prevent Problematic Movements of Industrial Workers Based on Inertial Sensors. | Cristiana Fernandes, Lus Miguel Matos, Duarte Folgado, Maria Lua Nunes, Joo Rui Pereira, Andr Luiz Pilastri, Paulo Cortez |
| 2022 | IDEAL | An Intelligent Decision Support System for Road Freight Transport. | Hugo Carvalho, Andr Luiz Pilastri, Arthur Matta, Lus Miguel Matos, Rui Novais, Paulo Cortez |
| 2022 | IDEAL | A Sequence to Sequence Long Short-Term Memory Network for Footwear Sales Forecasting. | Lus Santos, Lus Miguel Matos, Lus Ferreira, Pedro Alves, Mrio Viana, Andr Luiz Pilastri, Paulo Cortez |
| 2022 | KES | Predicting Yarn Breaks in Textile Fabrics: A Machine Learning Approach. | Joo Azevedo, Rui Ribeiro, Lus Miguel Matos, Rui Sousa, Joo Paulo Silva, Andr Luiz Pilastri, Paulo Cortez |
| 2021 | ICCSA | A Comparison of Anomaly Detection Methods for Industrial Screw Tightening. | Diogo Ribeiro, Lus Miguel Matos, Paulo Cortez, Guilherme Moreira, Andr Luiz Pilastri |
| 2021 | IDEAL | A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality. | Lus Miguel Matos, Andr Domingues, Guilherme Moreira, Paulo Cortez, Andr Luiz Pilastri |
| 2021 | KES | Using Deep Autoencoders for In-vehicle Audio Anomaly Detection. | Pedro Jos Pereira, Gabriel Coelho, Alexandrine Ribeiro, Lus Miguel Matos, Eduardo C. Nunes, Andr L. Ferreira, Andr Luiz Pilastri, Paulo Cortez |
| 2019 | IJCNN | Using Deep Learning for Mobile Marketing User Conversion Prediction. | Lus Miguel Matos, Paulo Cortez, Rui Mendes, Antoine Moreau |
| 2019 | IDEAL | Using Deep Learning for Ordinal Classification of Mobile Marketing User Conversion. | Lus Miguel Matos, Paulo Cortez, Rui Castro Mendes, Antoine Moreau |