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Cláudio M. S. Medeiros
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2020 – today
- 2021
- [j4]Rebeca Guerreiro Carvalho Cunha, Elias Teodoro da Silva Jr., Cláudio Marques de Sá Medeiros:
Machine learning and multiresolution decomposition for embedded applications to detect short-circuit in induction motors. Comput. Ind. 129: 103461 (2021) - 2020
- [c16]Carlos E. B. Sousa, Leonardo B. G. Nascimento, Cláudio M. S. Medeiros, Mauro Oliveira, Iago Avelino Trajano:
Decision Support Software for Melanoma Skin Cancer Detection (DECIME). AAI4H@ECAI 2020: 68-71
2010 – 2019
- 2019
- [j3]Pedro Pedrosa Rebouças Filho, Samuel Luz Gomes, Navar de Medeiros Mendonça e Nascimento, Cláudio Marques de Sá Medeiros, Fatma Outay, Victor Hugo C. de Albuquerque:
Energy production predication via Internet of Thing based machine learning system. Future Gener. Comput. Syst. 97: 180-193 (2019) - [c15]Diego P. Sousa, Guilherme A. Barreto, Charles C. Cavalcante, Cláudio M. S. Medeiros:
LVQ-type Classifiers for Condition Monitoring of Induction Motors: A Performance Comparison. WSOM+ 2019: 130-139 - 2018
- [j2]Pedro Pedrosa Rebouças Filho, Navar Medeiros M. e Nascimento, Igor Rocha de Sousa, Cláudio Marques de Sá Medeiros, Victor Hugo C. de Albuquerque:
A reliable approach for detection of incipient faults of short-circuits in induction generators using machine learning. Comput. Electr. Eng. 71: 440-451 (2018) - [c14]Pedro Pedrosa Rebouças Filho, Navar de Medeiros Mendonça e Nascimento, Shara Shami Araújo Alves, Samuel Luz Gomes, Cláudio Marques de Sá Medeiros:
Estimation of the Energy Production in a Wind Farm Using Regression Methods and Wind Speed Forecast. BRACIS 2018: 79-84 - [c13]Renato F. Pereira, Cláudio M. S. Medeiros, Pedro Pedrosa Rebouças Filho:
Goat Leather Quality Classification Using Computer Vision and Machine Learning. IJCNN 2018: 1-8 - [c12]Pedro Henrique Feijo de Sousa, Navar Medeiros M. e Nascimento, Pedro Pedrosa Rebouças Filho, Cláudio Marques de Sá Medeiros:
Detection and classification of faults in induction generator applied into wind turbines through a machine learning approach. IJCNN 2018: 1-7 - [c11]Igor Rocha de Sousa, Rogerio Vieira de Oliveira Segundo, Cláudio Marques de Sá Medeiros, Elias Teodoro Silva:
Estimation of global solar irradiance with LDR sensor and artificial neural network embedded in an 8-bit microcontroller. IJCNN 2018: 1-8 - [c10]Rebeca Guerreiro Carvalho Cunha, Elias Teodoro da Silva Júnior, Cláudio Marques de Sá Medeiros:
An Embedded Application to Identify Degradation in Energized Polymeric Insulators Using Machine Learning and Wavelet Transform. SBESC 2018: 46-53 - 2017
- [c9]Navar de Medeiros Mendonça e Nascimento, Cláudio Marques de Sá Medeiros, Pedro Pedrosa Rebouças Filho:
A Comparison of Machine Learning Methods to Identify Broken Bar Failures in Induction Motors Using Statistical Moments. ISDA 2017: 124-133 - [c8]David N. Coelho, Guilherme A. Barreto, Cláudio M. S. Medeiros:
Detection of short circuit faults in 3-phase converter-fed induction motors using kernel SOMs. WSOM 2017: 118-124 - 2016
- [c7]Renan Gomes Vieira, Cláudio M. S. Medeiros, Elias Teodoro Silva Jr.:
Classification and sensitivity analysis to detect fault in induction motors using an MLP network. IJCNN 2016: 796-802 - [c6]Renan Gomes Vieira, Rebeca Guerreiro C. Cunha, Cláudio Marques de Sá Medeiros, Elias Teodoro Silva Jr.:
Embedding a Neural Classifier to Detect Faults in a Three-Phase Induction Motor. SBESC 2016: 136-143 - 2014
- [c5]David N. Coelho, Guilherme De A. Barreto, Cláudio M. S. Medeiros, José Daniel Alencar Santos:
Performance comparison of classifiers in the detection of short circuit incipient fault in a three-phase induction motor. CIES 2014: 42-48 - 2013
- [j1]Cláudio M. S. Medeiros, Guilherme De A. Barreto:
A novel weight pruning method for MLP classifiers based on the MAXCORE principle. Neural Comput. Appl. 22(1): 71-84 (2013) - 2012
- [c4]David N. Coelho, Cláudio M. S. Medeiros:
Short Circuit Incipient Fault Detection and Supervision in a Three-Phase Induction Motor with a SOM-Based Algorithm. WSOM 2012: 315-323 - 2010
- [c3]José Daniel A. Santos, Guilherme De A. Barreto, Cláudio M. S. Medeiros:
Estimating the Number of Hidden Neurons of the MLP Using Singular Value Decomposition and Principal Components Analysis: A Novel Approach. SBRN 2010: 19-24
2000 – 2009
- 2007
- [c2]Cláudio M. S. Medeiros, Guilherme De A. Barreto:
An Efficient Method for Pruning the Multilayer Perceptron Based on the Correlation of Errors. ICANN (1) 2007: 219-228 - [c1]Cláudio M. S. Medeiros, Guilherme De A. Barreto:
Pruning the Multilayer Perceptron through the Correlation of Backpropagated Errors. ISDA 2007: 64-69
Coauthor Index
aka: Navar Medeiros M. e Nascimento
aka: Elias Teodoro da Silva Jr.
aka: Elias Teodoro da Silva Júnior
aka: Elias Teodoro Silva
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