André Luiz Pilastri

Publication Activity (10 Years)

Years Active: 2014-2023
Publications (10 Years): 34

Top Topics

Anomaly Detection

Machine Learning

Decision Support

Top Venues

Publications

Pedro José Pereira, Carlos Gonçalves, Lara Lopes Nunes, Paulo Cortez, André Luiz Pilastri
AI4CITY - An Automated Machine Learning Platform for Smart Cities. SAC (2023)
Paula Dias, Arthur Matta, André Luiz Pilastri, Luís Miguel Matos, Paulo Cortez
RTSIMU: Real-Time Simulation tool for IMU sensors. Softw. Impacts 17 (2023)
Luís Ferreira, Leopoldo Silva, Francisco Morais, Carlos Manuel Martins, Pedro Miguel Pires, Helena Rodrigues, Paulo Cortez, André Luiz Pilastri
International revenue share fraud prediction on the 5G edge using federated learning. Computing 105 (9) (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)
Rui Ribeiro, André Luiz Pilastri, Carla Moura, José Morgado, Paulo Cortez
A data-driven intelligent decision support system that combines predictive and prescriptive analytics for the design of new textile fabrics. Neural Comput. Appl. 35 (23) (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)
Hugo Carvalho, André Luiz Pilastri, Rui Novais, Paulo Cortez
RanCoord - A random geographic coordinates generator for transport and logistics research and development activities. Softw. Impacts 14 (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)
Afonso Sousa, Luís Ferreira, Rui Ribeiro, João Xavier, André Luiz Pilastri, Paulo Cortez
Production Time Prediction for Contract Manufacturing Industries Using Automated Machine Learning. AIAI (2) (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 Ferreira, André Luiz Pilastri, Filipe Romano, Paulo Cortez
Using supervised and one-class automated machine learning for predictive maintenance. Appl. Soft Comput. 131 (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)
Luís Ferreira, Leopoldo Silva, Diana Pinho, Francisco Morais, Carlos Manuel Martins, Pedro Miguel Pires, Pedro Fidalgo, Helena Rodrigues, Paulo Cortez, André Luiz Pilastri
A federated machine learning approach to detect international revenue share fraud on the 5G edge. SAC (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)
Pedro José Pereira, Adriana Pereira, Paulo Cortez, André Luiz Pilastri
A Comparison of Machine Learning Methods for Extremely Unbalanced Industrial Quality Data. EPIA (2021)
Luís Ferreira, André Luiz Pilastri, Vítor Sousa, Filipe Romano, Paulo Cortez
Prediction of Maintenance Equipment Failures Using Automated Machine Learning. IDEAL (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 Ferreira, André Luiz Pilastri, Carlos Manuel Martins, Pedro Miguel Pires, Paulo Cortez
A Comparison of AutoML Tools for Machine Learning, Deep Learning and XGBoost. IJCNN (2021)
Rui Ribeiro, André Luiz Pilastri, Hugo Carvalho, Arthur Matta, Pedro José Pereira, Pedro Rocha, Marcelo Alves, Paulo Cortez
An Intelligent Decision Support System for Production Planning in Garments Industry. IDEAL (2021)
António João Silva, Paulo Cortez, Carlos Pereira, André Luiz Pilastri
Business analytics in Industry 4.0: A systematic review. Expert Syst. J. Knowl. Eng. 38 (7) (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)
Rui Ribeiro, André Luiz Pilastri, Carla Moura, Filipe Rodrigues, Rita Rocha, Paulo Cortez
Predicting the Tear Strength of Woven Fabrics Via Automated Machine Learning: An Application of the CRISP-DM Methodology. ICEIS (1) (2020)
Luís Ferreira, André Luiz Pilastri, Carlos Martins, Pedro Santos, Paulo Cortez
A Scalable and Automated Machine Learning Framework to Support Risk Management. ICAART (Revised Selected Papers) (2020)
Luís Ferreira, André Luiz Pilastri, Carlos Martins, Pedro Santos, Paulo Cortez
An Automated and Distributed Machine Learning Framework for Telecommunications Risk Management. ICAART (2) (2020)
António João Silva, Paulo Cortez, André Luiz Pilastri
Chemical Laboratories 4.0: A Two-Stage Machine Learning System for Predicting the Arrival of Samples. AIAI (2) (2020)
Rui Ribeiro, André Luiz Pilastri, Carla Moura, Filipe Rodrigues, Rita Rocha, José Morgado, Paulo Cortez
Predicting Physical Properties of Woven Fabrics via Automated Machine Learning and Textile Design and Finishing Features. AIAI (2) (2020)
Juliana Cassiano Ferrarezi, Mário Popolin Neto, Diego Roberto Colombo Dias, André Luiz Pilastri, Marcelo de Paiva Guimarães, José Remo Ferreira Brega
LibViews - An Information Visualization Application for Third-Party Libraries on Software Projects. IV (2016)
Silas Evandro Nachif Fernandes, André Luiz Pilastri, Luís A. M. Pereira, Rafael Goncalves Pires, João Paulo Papa
Learning Kernels for Support Vector Machines with Polynomial Powers of Sigmoid. SIBGRAPI (2014)