Algoritmi | User | Luís Miguel da Rocha de Matos
Luís Miguel da Rocha de Matos
Luís Miguel da Rocha de Matos
At Algoritmi
Research Collaborator with MSc
Member of the IST R&D Group
Academic Degree
MSc
Current Position
Other at Escola de Engenharia da Universidade do Minho
Personal Webpage
Personal Email
luis.matos@dsi.uminho.ptOrcid
0000-0001-5827-9129Researcher ID
N-8043-2015FCT Public Key
J64911226d44
Ciência ID
4B15-8E29-1D57Google Scholar
About Me 
Publications (9)
A Comparison of Anomaly Detection Methods for Industrial Screw Tightening
Computational Science and Its Applications - ICCSA 2021 - 21st International Conference, Cagliari, Italy, September 13-16, 2021, Proceedings, Part II
2021 | conference-paper
A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality
Intelligent Data Engineering and Automated Learning – IDEAL 2021
2021 | book-chapter
Deep Dense and Convolutional Autoencoders for Machine Acoustic Anomaly Detection
2021 | book-chapter
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds
2020 | preprint
A Categorical Clustering of Publishers for Mobile Performance Marketing
Advances in Intelligent Systems and Computing
2019 | book
Using Deep Learning for Mobile Marketing User Conversion Prediction
Proceedings of the International Joint Conference on Neural Networks
2019 | conference-paper
Using Deep Learning for Ordinal Classification of Mobile Marketing User Conversion
Intelligent Data Engineering and Automated Learning – IDEAL 2019
2019 | book-chapter
Forecasting store foot traffic using facial recognition, time series and support vector machines
Advances in Intelligent Systems and Computing
2017 | book
Forecasting Human Entrances at a Commercial Store using facial recognition data
2015 | dissertation-thesis
A Comparison of Anomaly Detection Methods for Industrial Screw Tightening
Computational Science and Its Applications - ICCSA 2021 - 21st International Conference, Cagliari, Italy, September 13-16, 2021, Proceedings, Part II
2021 | conference-paper
A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality
Intelligent Data Engineering and Automated Learning – IDEAL 2021
2021 | book-chapter
Deep Dense and Convolutional Autoencoders for Machine Acoustic Anomaly Detection
2021 | book-chapter
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds
2020 | preprint
A Categorical Clustering of Publishers for Mobile Performance Marketing
Advances in Intelligent Systems and Computing
2019 | book
Using Deep Learning for Mobile Marketing User Conversion Prediction
Proceedings of the International Joint Conference on Neural Networks
2019 | conference-paper
Using Deep Learning for Ordinal Classification of Mobile Marketing User Conversion
Intelligent Data Engineering and Automated Learning – IDEAL 2019
2019 | book-chapter
Forecasting store foot traffic using facial recognition, time series and support vector machines
Advances in Intelligent Systems and Computing
2017 | book
Forecasting Human Entrances at a Commercial Store using facial recognition data
2015 | dissertation-thesis
