This user account status is Approved
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.pt

Orcid

0000-0001-5827-9129

Researcher ID

N-8043-2015

FCT Public Key

J64911226d44

Ciência ID

4B15-8E29-1D57

Google Scholar

About Me



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