Luís Miguel Matos

27 papers B 6C 3Misc 1Journal 8Unranked 8
YearRankTypeTitle / Venue / Authors
2026 B conf
An End-to-End Framework for Measuring Product Cannibalization Using Multivariate Time Series Forecasting.
IDA
Daniela Martins, Luís Miguel Matos
2025 J jnl
Screw Process Anomaly Visualization (SPAV): A Python module for local and global machine learning visualizations for screw tightening anomaly detection.
Softw. Impacts
Marta Moreno, Hugo Rocha, André Luiz Pilastri, Guilherme Moreira, Luís Miguel Matos, Paulo Cortez
2024 B conf
Ahead of Time Prediction of Decorated Particleboard Production Disruptions and Defects Using Single and Multi-Target AutoML.
KES
Arthur Matta, Luís Miguel Matos, André Luiz Pilastri, Jorge Miguel Silva, Miguel Bastos Gomes, Paulo Cortez
2024 J jnl
Proactive prevention of work-related musculoskeletal disorders using a motion capture system and time series machine learning.
Eng. Appl. Artif. Intell.
Luís Miguel Matos, Paula Dias, Arthur Matta, Dário Machado, Rosane Sampaio, André Luiz Pilastri, Paulo Cortez
2023 J jnl
A Deep Learning-Based Decision Support System for Mobile Performance Marketing.
Int. J. Inf. Technol. Decis. Mak.
Luís Miguel Matos, Paulo Cortez, Rui Mendes, Antoine Moreau
2023 — conf
Machine Learning for Predicting Production Disruptions in the Wood-Based Panels Industry: A Demonstration Case.
AIAI (2)
Cláudia Afonso, Arthur Matta, Luís Miguel Matos, Miguel Bastos Gomes, Antonina Santos, André Luiz Pilastri, Paulo Cortez
2023 J jnl
RTSIMU: Real-Time Simulation tool for IMU sensors.
Softw. Impacts
Paula Dias, Arthur Matta, André Luiz Pilastri, Luís Miguel Matos, Paulo Cortez
2022 B conf
A Deep Learning Approach to Prevent Problematic Movements of Industrial Workers Based on Inertial Sensors.
IJCNN
Cristiana Fernandes, Luís Miguel Matos, Duarte Folgado, Maria Lua Nunes, João Rui Pereira, André Luiz Pilastri, Paulo Cortez
2022 — conf
A Machine Learning Approach for Spare Parts Lifetime Estimation.
ICAART (3)
Luísa Macedo, Luís Miguel Matos, Paulo Cortez, André Domingues, Guilherme Moreira, André Luiz Pilastri
2022 C conf
A Sequence to Sequence Long Short-Term Memory Network for Footwear Sales Forecasting.
IDEAL
Luís Santos, Luís Miguel Matos, Luís Ferreira, Pedro Alves, Mário Viana, André Luiz Pilastri, Paulo Cortez
2022 — conf
An Empirical Study on Anomaly Detection Algorithms for Extremely Imbalanced Datasets.
AIAI (1)
Gonçalo Fontes, Luís Miguel Matos, Arthur Matta, André Luiz Pilastri, Paulo Cortez
2022 C conf
An Intelligent Decision Support System for Road Freight Transport.
IDEAL
Hugo Carvalho, André Luiz Pilastri, Arthur Matta, Luís Miguel Matos, Rui Novais, Paulo Cortez
2022 J jnl
Categorical Attribute traNsformation Environment (CANE): A python module for categorical to numeric data preprocessing.
Softw. Impacts
Luís Miguel Matos, João Azevedo, Arthur Matta, André Luiz Pilastri, Paulo Cortez, Rui Mendes
2022 J jnl
Deep autoencoders for acoustic anomaly detection: experiments with working machine and in-vehicle audio.
Neural Comput. Appl.
Gabriel Coelho, Luís Miguel Matos, Pedro José Pereira, André L. Ferreira, André Luiz Pilastri, Paulo Cortez
2022 J jnl
Isolation Forests and Deep Autoencoders for Industrial Screw Tightening Anomaly Detection.
Comput.
Diogo Ribeiro, Luís Miguel Matos, Guilherme Moreira, André Luiz Pilastri, Paulo Cortez
2022 B conf
Predicting Yarn Breaks in Textile Fabrics: A Machine Learning Approach.
KES
João Azevedo, Rui Ribeiro, Luís Miguel Matos, Rui Sousa, João Paulo Silva, André Luiz Pilastri, Paulo Cortez
2021 — conf
A Comparison of Anomaly Detection Methods for Industrial Screw Tightening.
ICCSA (2)
Diogo Ribeiro, Luís Miguel Matos, Paulo Cortez, Guilherme Moreira, André Luiz Pilastri
2021 C conf
A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality.
IDEAL
Luís Miguel Matos, André Domingues, Guilherme Moreira, Paulo Cortez, André Luiz Pilastri
2021 — —
An intelligent decision support system for mobile performance marketing
Luís Miguel Matos
2021 Misc conf
Deep Dense and Convolutional Autoencoders for Machine Acoustic Anomaly Detection.
AIAI
Gabriel Coelho, Pedro José Pereira, Luís Miguel Matos, Alexandrine Ribeiro, Eduardo C. Nunes, André L. Ferreira, Paulo Cortez, André Luiz Pilastri
2021 B conf
Using Deep Autoencoders for In-vehicle Audio Anomaly Detection.
KES
Pedro José Pereira, Gabriel Coelho, Alexandrine Ribeiro, Luís Miguel Matos, Eduardo C. Nunes, André L. Ferreira, André Luiz Pilastri, Paulo Cortez
2020 J jnl
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds.
CoRR
Alexandrine Ribeiro, Luís Miguel Matos, Pedro José Pereira, Eduardo C. Nunes, André L. Ferreira, Paulo Cortez, André Luiz Pilastri
2019 B conf
Using Deep Learning for Mobile Marketing User Conversion Prediction.
IJCNN
Luís Miguel Matos, Paulo Cortez, Rui Mendes, Antoine Moreau
2019 — conf
Using Deep Learning for Ordinal Classification of Mobile Marketing User Conversion.
IDEAL (1)
Luís Miguel Matos, Paulo Cortez, Rui Castro Mendes, Antoine Moreau
2018 — conf
A Categorical Clustering of Publishers for Mobile Performance Marketing.
SOCO-CISIS-ICEUTE
Susana Silva, Paulo Cortez, Rui Mendes, Pedro José Pereira, Luís Miguel Matos, Luís Garcia
2018 — conf
A Comparison of Data-Driven Approaches for Mobile Marketing User Conversion Prediction.
IEEE Conf. on Intelligent Systems
Luís Miguel Matos, Paulo Cortez, Rui Mendes, Antoine Moreau
2016 — conf
Forecasting Store Foot Traffic Using Facial Recognition, Time Series and Support Vector Machines.
SOCO-CISIS-ICEUTE
Paulo Cortez, Luís Miguel Matos, Pedro José Pereira, Nuno Santos, Duarte Duque