André Eugênio Lazzaretti - LACTEC, Curitiba, Brazil;c;LACTEC

基本信息

Career Trajectory

Bio

André Eugenio Lazzaretti (Member, IEEE) received the B.Sc., M.Sc., and D.Sc. degrees in electrical engineering from the Federal University of Technology–Paraná, Curitiba, Brazil, in 2007, 2010, and 2015, respectively. He is currently a Professor with the Department of Electronics, Federal University of Technology–Paraná. His research interests include machine learning, deep learning, and digital signal processing.

Research Interests

Papers共 110 篇Author StatisticsCo-AuthorSimilar Experts

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ST-NILM: A Wavelet Scattering-Based Architecture for Feature Extraction and Multi-Label Classification in NILM Signals

Everton Luiz De Aguiar,Lucas da Silva Nolasco,André Eugenio Lazzaretti,Daniel Rodrigues Pipa,Heitor Silvério Lopes

IEEE Sensors Journalno. 99 (2024): 1-1

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Correction: A New Lumped Parameter Modeling for Wind Farm Grounding Measurement Circuits Based on Clamp-on Ground Meters

Alexandre Giacomelli Leal,André E. Lazzaretti, Henry L. López-Salamanca

Journal of Control, Automation and Electrical Systemspp.1-1, (2024)

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Enhanced estimation of wind turbine grounding resistance using clamp-on metering, computational simulation, and machine learning techniques

Alexandre Giacomelli Leal,André Eugenio Lazzaretti,Henry Leonardo López-Salamanca

Electric Power Systems Research (2024): 110942

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An industrial edge computing architecture for Local Digital Twin

Ricardo Eiji Kondo, Willian Jeferson Andrade,Clayton de Mello Henequim,André Eugenio Lazzaretti, Alceu de Souza Britto,Eduardo de Freitas Rocha Loures,Eduardo Alves Portela Santos,Gilberto Reynoso-Meza

Computers & Industrial Engineering (2024): 110257

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Edge Device for the Classification of Photovoltaic Faults Using Deep Neural Networks

André Biffe Di Renzo, Héber Renato Fadel de Morais,André Eugenio Lazzaretti, Lúcia Valéria Ramos de Arruda, Heitor Silvério Lopes, Cicero Martelli, Jean Carlos Cardozo da Silva

Journal of Control, Automation and Electrical Systemspp.1-9, (2024)

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Usage of Harmonic Synchrophasors for High-Impedance Fault Classification in Microgrids

Dionatan A. G. Cieslak,Miguel Moreto,André E. Lazzaretti, José R. M. Junior,Flávio L. Grando, Tiago N. Siemann

Journal of Control, Automation and Electrical Systemsno. 3 (2024): 1-14

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Event-Driven sEMG Feature Extraction for Classifying Ingestive Behavior in Ruminants

Daniel P. Campos,André E. Lazzaretti,Fábio L. Bertotti,João A. G. Hill,André L. F. da Silveira

IEEE Sensors Lettersno. 99 (2024): 1-4

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Machine Learning-Based Methods for Force Mapping With an Optical Fiber Sensing System

Walter Oswaldo Cutipa Flores, Vinícius Carvalho, Victor Hugo Martins,José Luís Fabris,Marcia Muller,Heitor Silvério Lopes,André Eugenio Lazzaretti

IEEE Sensors Lettersno. 99 (2024): 1-4

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High impedance fault classification in microgrids using a transformer-based model with time series harmonic synchrophasors under data quality issues

Dionatan A. G. Cieslak,Miguel Moreto,André E. Lazzaretti, José R. Macedo-Júnior

Neural Computing and Applicationspp.1-18, (2024)

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Recognition, location, and depth estimation of objects in electrical substations

Gilberto Lexinoski,Marco A. S. Teixeira,Andre E. Lazzaretti, Luiz F. R. B. Toledo,Heitor S. Lopes,Gustavo Travassos, Mario Jambeiro Fonseca

2023 LATIN AMERICAN ROBOTICS SYMPOSIUM, LARS, 2023 BRAZILIAN SYMPOSIUM ON ROBOTICS, SBR, AND 2023 WORKSHOP ON ROBOTICS IN EDUCATION, WREpp.427-432, (2023)

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