Luís Miguel Matos

According to our database, Luís Miguel Matos authored at least 23 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

RTSIMU: Real-Time Simulation tool for IMU sensors.

Paula Dias, Arthur Matta, André Luiz Pilastri, Luís Miguel Matos, Paulo Cortez

Softw. Impacts, September, 2023

A Deep Learning-Based Decision Support System for Mobile Performance Marketing.

Luís Miguel Matos, Paulo Cortez, Rui Mendes, Antoine Moreau

Int. J. Inf. Technol. Decis. Mak., March, 2023

Machine Learning for Predicting Production Disruptions in the Wood-Based Panels Industry: A Demonstration Case.

Cláudia Afonso, Arthur Matta, Luís Miguel Matos, Miguel Bastos Gomes, Antonina Santos, André Luiz Pilastri, Paulo Cortez

Proceedings of the Artificial Intelligence Applications and Innovations, 2023

2022

Categorical Attribute traNsformation Environment (CANE): A python module for categorical to numeric data preprocessing.

Luís Miguel Matos, João Azevedo, Arthur Matta, André Luiz Pilastri, Paulo Cortez, Rui Mendes

Softw. Impacts, 2022

Deep autoencoders for acoustic anomaly detection: experiments with working machine and in-vehicle audio.

Gabriel Coelho, Luís Miguel Matos, Pedro José Pereira, André L. Ferreira, André Luiz Pilastri, Paulo Cortez

Neural Comput. Appl., 2022

Isolation Forests and Deep Autoencoders for Industrial Screw Tightening Anomaly Detection.

Diogo Ribeiro, Luís Miguel Matos, Guilherme Moreira, André Luiz Pilastri, Paulo Cortez

Comput., 2022

Predicting Yarn Breaks in Textile Fabrics: A Machine Learning Approach.

João Azevedo, Rui Ribeiro, Luís Miguel Matos, Rui Sousa, João Paulo Silva, André Luiz Pilastri, Paulo Cortez

Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 26th International Conference KES-2022, 2022

A Deep Learning Approach to Prevent Problematic Movements of Industrial Workers Based on Inertial Sensors.

Cristiana Fernandes, Luís Miguel Matos, Duarte Folgado, Maria Lua Nunes, João Rui Pereira, André Luiz Pilastri, Paulo Cortez

Proceedings of the International Joint Conference on Neural Networks, 2022

An Empirical Study on Anomaly Detection Algorithms for Extremely Imbalanced Datasets.

Gonçalo Fontes, Luís Miguel Matos, Arthur Matta, André Luiz Pilastri, Paulo Cortez

Proceedings of the Artificial Intelligence Applications and Innovations, 2022

A Sequence to Sequence Long Short-Term Memory Network for Footwear Sales Forecasting.

Luís Santos, Luís Miguel Matos, Luís Ferreira, Pedro Alves, Mário Viana, André Luiz Pilastri, Paulo Cortez

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2022, 2022

An Intelligent Decision Support System for Road Freight Transport.

Hugo Carvalho, André Luiz Pilastri, Arthur Matta, Luís Miguel Matos, Rui Novais, Paulo Cortez

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2022, 2022

A Machine Learning Approach for Spare Parts Lifetime Estimation.

Luísa Macedo, Luís Miguel Matos, Paulo Cortez, André Domingues, Guilherme Moreira, André Luiz Pilastri

Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022

2021

An intelligent decision support system for mobile performance marketing

Luís Miguel Matos

PhD thesis, 2021

Using Deep Autoencoders for In-vehicle Audio Anomaly Detection.

Pedro José Pereira, Gabriel Coelho, Alexandrine Ribeiro, Luís Miguel Matos, Eduardo C. Nunes, André L. Ferreira, André Luiz Pilastri, Paulo Cortez

Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES-2021, 2021

Deep Dense and Convolutional Autoencoders for Machine Acoustic Anomaly Detection.

Gabriel Coelho, Pedro José Pereira, Luís Miguel Matos, Alexandrine Ribeiro, Eduardo C. Nunes, André L. Ferreira, Paulo Cortez, André Luiz Pilastri

Proceedings of the Artificial Intelligence Applications and Innovations, 2021

A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality.

Luís Miguel Matos, André Domingues, Guilherme Moreira, Paulo Cortez, André Luiz Pilastri

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2021, 2021

A Comparison of Anomaly Detection Methods for Industrial Screw Tightening.

Diogo Ribeiro, Luís Miguel Matos, Paulo Cortez, Guilherme Moreira, André Luiz Pilastri

Proceedings of the Computational Science and Its Applications - ICCSA 2021, 2021

2020

Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds.

Alexandrine Ribeiro, Luís Miguel Matos, Pedro José Pereira, Eduardo C. Nunes, André L. Ferreira, Paulo Cortez, André Luiz Pilastri

CoRR, 2020

2019

Using Deep Learning for Mobile Marketing User Conversion Prediction.

Luís Miguel Matos, Paulo Cortez, Rui Mendes, Antoine Moreau

Proceedings of the International Joint Conference on Neural Networks, 2019

Using Deep Learning for Ordinal Classification of Mobile Marketing User Conversion.

Luís Miguel Matos, Paulo Cortez, Rui Castro Mendes, Antoine Moreau

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

2018

A Categorical Clustering of Publishers for Mobile Performance Marketing.

Susana Silva, Paulo Cortez, Rui Mendes, Pedro José Pereira, Luís Miguel Matos, Luís Garcia

Proceedings of the International Joint Conference SOCO'18-CISIS'18-ICEUTE'18, 2018

A Comparison of Data-Driven Approaches for Mobile Marketing User Conversion Prediction.

Luís Miguel Matos, Paulo Cortez, Rui Mendes, Antoine Moreau

Proceedings of the 9th IEEE International Conference on Intelligent Systems, 2018

2016

Forecasting Store Foot Traffic Using Facial Recognition, Time Series and Support Vector Machines.

Paulo Cortez, Luís Miguel Matos, Pedro José Pereira, Nuno Santos, Duarte Duque

Proceedings of the International Joint Conference SOCO'16-CISIS'16-ICEUTE'16, 2016