Telmo de Menezes e Silva Filho

According to our database, Telmo de Menezes e Silva Filho authored at least 36 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Sighted particles: improving swarm optimization by making particles aware of their surroundings.

Wagner J. F. Silva, Telmo de Menezes e Silva Filho, Delmiro D. Sampaio Neto, Renata M. C. R. Souza, Adriano L. I. Oliveira, Francisco José de A. Cysneiros

Evol. Intell., April, 2024

Assessment of volumetric dense tissue segmentation in tomosynthesis using deep virtual clinical trials.

Bruno Barufaldi, Jordy V. Gomes, Telmo de Menezes e Silva Filho, Thaís Gaudencio do Rêgo, Yuri Malheiros, Trevor Lewis Vent, Aimilia Gastounioti, Andrew D. A. Maidment

Pattern Recognit., 2024

Time-Series Classification for Dynamic Strategies in Multi-Step Forecasting.

Riku Green, Grant Stevens, Telmo de Menezes e Silva Filho, Zahraa S. Abdallah

CoRR, 2024

Towards explainable evaluation: Explaining predicted performance using local performance regions.

Patrícia Drapal, Ricardo B. C. Prudêncio, Telmo de Menezes e Silva Filho

Appl. Soft Comput., 2024

Assessor Models for Explaining Instance Hardness in Classification Problems.

Ricardo B. C. Prudêncio, Ana Carolina Lorena, Telmo de Menezes e Silva Filho, Patrícia Drapal, Maria Gabriela Valeriano

Proceedings of the International Joint Conference on Neural Networks, 2024

Meta-Learning and Novelty Detection for Machine Learning with Reject Option.

Patrícia Drapal, Telmo de Menezes e Silva Filho, Ricardo B. C. Prudêncio

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

Classifying breast lesions in Brazilian thermographic images using convolutional neural networks.

Flávia R. S. Brasileiro, Delmiro D. Sampaio Neto, Telmo de Menezes e Silva Filho, Renata M. C. R. de Souza, Marcus C. de Araújo

Neural Comput. Appl., September, 2023

Classifier calibration: a survey on how to assess and improve predicted class probabilities.

Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach

Mach. Learn., September, 2023

β⁴-IRT: A New β³-IRT with Enhanced Discrimination Estimation.

Manuel Ferreira Junior, Jessica T. S. Reinaldo, Telmo de Menezes e Silva Filho, Eufrasio A. Lima Neto, Ricardo B. C. Prudêncio

CoRR, 2023

2022

A two-level Item Response Theory model to evaluate speech synthesis and recognition.

Chaina Santos Oliveira, João V. C. Moraes, Telmo de Menezes e Silva Filho, Ricardo B. C. Prudêncio

Speech Commun., 2022

Evaluating regression algorithms at the instance level using item response theory.

João V. C. Moraes, Jessica T. S. Reinaldo, Manuel Ferreira Junior, Telmo de Menezes e Silva Filho, Ricardo B. C. Prudêncio

Knowl. Based Syst., 2022

Learning Under Concept Drift for Regression - A Systematic Literature Review.

Marília Lima, Manoel Alves de Almeida Neto, Telmo de Menezes e Silva Filho, Roberta A. de A. Fagundes

IEEE Access, 2022

Evaluating Data Representations for Object Recognition During Pick-and-Place Manipulation Tasks.

Humberto Navarro de Carvalho, Lucas Pontes Castro, Thaís Gaudencio do Rêgo, Telmo de Menezes e Silva Filho, Yuri de A. M. Barbosa, Leonardo Vidal Batista, Amílcar Soares, Vinicius Prado da Fonseca

Proceedings of the IEEE International Systems Conference, 2022

Automatic Recognition of Units of Measurement in Product Descriptions from Tax Invoices Using Neural Networks.

Lucas Fernandes Lucena, Telmo de Menezes e Silva Filho, Thaís Gaudencio do Rêgo, Yuri Malheiros

Proceedings of the Computational Processing of the Portuguese Language, 2022

Explaining Learning Performance with Local Performance Regions and Maximally Relevant Meta-Rules.

Ricardo B. C. Prudêncio, Telmo de Menezes e Silva Filho

Proceedings of the Intelligent Systems - 11th Brazilian Conference, 2022

2021

Kohonen map-wise regression applied to interval data.

Leandro Carlos de Souza, Bruno A. Pimentel, Telmo de Menezes e Silva Filho, Renata M. C. R. de Souza

Knowl. Based Syst., 2021

Classifier Calibration: How to assess and improve predicted class probabilities: a survey.

Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach

CoRR, 2021

A Comparative Study on Concept Drift Detectors for Regression.

Marília Lima, Telmo de Menezes e Silva Filho, Roberta Fagundes

Proceedings of the Intelligent Systems - 10th Brazilian Conference, 2021

Iris-CV: Classifying Iris Flowers Is Not as Easy as You Thought.

Itamar Rocha Filho, João Pedro Vasconcelos Teixeira, João Wallace Lucena Lins, Felipe Honorato de Sousa, Ana Clara Chaves Sousa, Manuel Ferreira Junior, Thaís Ramos, Cecília Silva, Thaís Gaudencio do Rêgo, Yuri de Almeida Malheiros, Telmo de Menezes e Silva Filho

Proceedings of the Intelligent Systems - 10th Brazilian Conference, 2021

Automatic Segmentation of Mammary Tissue using Computer Simulations of Breast Phantoms and Deep-learning Techniques.

Lucca R. Peregrino, Jordy V. Gomes, Thaís Gaudencio do Rêgo, Yuri de A. M. Barbosa, Telmo de Menezes e Silva Filho, Andrew D. A. Maidment, Bruno Barufaldi

Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, 2021

2020

Item Response Theory for Evaluating Regression Algorithms.

João V. C. Moraes, Jessica T. S. Reinaldo, Ricardo B. C. Prudêncio, Telmo de Menezes e Silva Filho

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

Investigating different fitness criteria for swarm-based clustering.

Maria Priscila Da Silva Souza, Telmo de Menezes e Silva Filho, Getúlio José Amorim do Amaral, Renata Maria Cardoso Rodrigues De Souza

Int. J. Bus. Intell. Data Min., 2019

Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration.

Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach

CoRR, 2019

β³-IRT: A New Item Response Model and its Applications.

Yu Chen, Telmo de Menezes e Silva Filho, Ricardo B. C. Prudêncio, Tom Diethe, Peter A. Flach

CoRR, 2019

Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration.

Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

$β^3$-IRT: A New Item Response Model and its Applications.

Yu Chen, Telmo de Menezes e Silva Filho, Ricardo B. C. Prudêncio, Tom Diethe, Peter A. Flach

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2017

An interval prototype classifier based on a parameterized distance applied to breast thermographic images.

Marcus C. Araújo, Renata M. C. R. Souza, Rita C. F. Lima, Telmo de Menezes e Silva Filho

Medical Biol. Eng. Comput., 2017

A parametrized approach for linear regression of interval data.

Leandro Carlos de Souza, Renata M. C. R. Souza, Getúlio J. A. Amaral, Telmo de Menezes e Silva Filho

Knowl. Based Syst., 2017

Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers.

Meelis Kull, Telmo de Menezes e Silva Filho, Peter A. Flach

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

A swarm-trained k-nearest prototypes adaptive classifier with automatic feature selection for interval data.

Telmo de Menezes e Silva Filho, Renata M. C. R. Souza, Ricardo B. C. Prudêncio

Neural Networks, 2016

Background Check: A General Technique to Build More Reliable and Versatile Classifiers.

Miquel Perelló-Nieto, Telmo de Menezes e Silva Filho, Meelis Kull, Peter A. Flach

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015

Hybrid methods for fuzzy clustering based on fuzzy c-means and improved particle swarm optimization.

Telmo de Menezes e Silva Filho, Bruno A. Pimentel, Renata M. C. R. Souza, Adriano L. I. Oliveira

Expert Syst. Appl., 2015

2013

Fuzzy learning vector quantization approaches for interval data.

Telmo de Menezes e Silva Filho, Renata M. C. R. Souza

Proceedings of the FUZZ-IEEE 2013, 2013

2012

A Weighted Learning Vector Quantization Approach for Interval Data.

Telmo de Menezes e Silva Filho, Renata Maria Cardoso R. de Souza

Proceedings of the Neural Information Processing - 19th International Conference, 2012

2011

Pattern classifiers with adaptive distances.

Telmo de Menezes e Silva Filho, Renata M. C. R. de Souza

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

2009

Optimized Learning Vector Quantization Classifier with an Adaptive Euclidean Distance.

Renata M. C. R. de Souza, Telmo de Menezes e Silva Filho

Proceedings of the Artificial Neural Networks, 2009