Luís Miguel Matos

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 22

Top Topics

Imbalanced Datasets

Ordinal Classification

Anomaly Detection

Top Venues

SOCO-CISIS-ICEUTE

Publications

Paula Dias, Arthur Matta, André Luiz Pilastri, Luís Miguel Matos, Paulo Cortez
RTSIMU: Real-Time Simulation tool for IMU sensors. Softw. Impacts 17 (2023)
Cláudia Afonso, Arthur Matta, Luís Miguel Matos, Miguel Bastos Gomes, Antonina Santos, André Luiz Pilastri, Paulo Cortez
Machine Learning for Predicting Production Disruptions in the Wood-Based Panels Industry: A Demonstration Case. AIAI (2) (2023)
Luís Miguel Matos, Paulo Cortez, Rui Mendes, Antoine Moreau
A Deep Learning-Based Decision Support System for Mobile Performance Marketing. Int. J. Inf. Technol. Decis. Mak. 22 (2) (2023)
Hugo Carvalho, André Luiz Pilastri, Arthur Matta, Luís Miguel Matos, Rui Novais, Paulo Cortez
An Intelligent Decision Support System for Road Freight Transport. IDEAL (2022)
João Azevedo, Rui Ribeiro, Luís Miguel Matos, Rui Sousa, João Paulo Silva, André Luiz Pilastri, Paulo Cortez
Predicting Yarn Breaks in Textile Fabrics: A Machine Learning Approach. KES (2022)
Cristiana Fernandes, Luís Miguel Matos, Duarte Folgado, Maria Lua Nunes, João Rui Pereira, André Luiz Pilastri, Paulo Cortez
A Deep Learning Approach to Prevent Problematic Movements of Industrial Workers Based on Inertial Sensors. IJCNN (2022)
Diogo Ribeiro, Luís Miguel Matos, Guilherme Moreira, André Luiz Pilastri, Paulo Cortez
Isolation Forests and Deep Autoencoders for Industrial Screw Tightening Anomaly Detection. Comput. 11 (4) (2022)
Gonçalo Fontes, Luís Miguel Matos, Arthur Matta, André Luiz Pilastri, Paulo Cortez
An Empirical Study on Anomaly Detection Algorithms for Extremely Imbalanced Datasets. AIAI (1) (2022)
Luís Miguel Matos, João Azevedo, Arthur Matta, André Luiz Pilastri, Paulo Cortez, Rui Mendes
Categorical Attribute traNsformation Environment (CANE): A python module for categorical to numeric data preprocessing. Softw. Impacts 13 (2022)
Luísa Macedo, Luís Miguel Matos, Paulo Cortez, André Domingues, Guilherme Moreira, André Luiz Pilastri
A Machine Learning Approach for Spare Parts Lifetime Estimation. ICAART (3) (2022)
Luís Santos, Luís Miguel Matos, Luís Ferreira, Pedro Alves, Mário Viana, André Luiz Pilastri, Paulo Cortez
A Sequence to Sequence Long Short-Term Memory Network for Footwear Sales Forecasting. IDEAL (2022)
Gabriel Coelho, Luís Miguel Matos, Pedro José Pereira, André L. Ferreira, André Luiz Pilastri, Paulo Cortez
Deep autoencoders for acoustic anomaly detection: experiments with working machine and in-vehicle audio. Neural Comput. Appl. 34 (22) (2022)
Diogo Ribeiro, Luís Miguel Matos, Paulo Cortez, Guilherme Moreira, André Luiz Pilastri
A Comparison of Anomaly Detection Methods for Industrial Screw Tightening. ICCSA (2) (2021)
Gabriel Coelho, Pedro Pereira, Luís Miguel Matos, Alexandrine Ribeiro, Eduardo C. Nunes, André L. Ferreira, Paulo Cortez, André Luiz Pilastri
Deep Dense and Convolutional Autoencoders for Machine Acoustic Anomaly Detection. AIAI (2021)
Pedro José Pereira, Gabriel Coelho, Alexandrine Ribeiro, Luís Miguel Matos, Eduardo C. Nunes, André L. Ferreira, André Luiz Pilastri, Paulo Cortez
Using Deep Autoencoders for In-vehicle Audio Anomaly Detection. KES (2021)
Luís Miguel Matos, André Domingues, Guilherme Moreira, Paulo Cortez, André Luiz Pilastri
A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality. IDEAL (2021)
Alexandrine Ribeiro, Luís Miguel Matos, Pedro José Pereira, Eduardo C. Nunes, André L. Ferreira, Paulo Cortez, André Luiz Pilastri
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds. CoRR (2020)
Luís Miguel Matos, Paulo Cortez, Rui Mendes, Antoine Moreau
Using Deep Learning for Mobile Marketing User Conversion Prediction. IJCNN (2019)
Luís Miguel Matos, Paulo Cortez, Rui Castro Mendes, Antoine Moreau
Using Deep Learning for Ordinal Classification of Mobile Marketing User Conversion. IDEAL (1) (2019)
Susana Silva, Paulo Cortez, Rui Mendes, Pedro José Pereira, Luís Miguel Matos, Luís Garcia
A Categorical Clustering of Publishers for Mobile Performance Marketing. SOCO-CISIS-ICEUTE (2018)
Luís Miguel Matos, Paulo Cortez, Rui Mendes, Antoine Moreau
A Comparison of Data-Driven Approaches for Mobile Marketing User Conversion Prediction. IEEE Conf. on Intelligent Systems (2018)
Paulo Cortez, Luís Miguel Matos, Pedro José Pereira, Nuno Santos, Duarte Duque
Forecasting Store Foot Traffic Using Facial Recognition, Time Series and Support Vector Machines. SOCO-CISIS-ICEUTE (2016)