Mateus Roder

According to our database, Mateus Roder authored at least 30 papers between 2020 and 2024.

Collaborative distances:

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

2024

Adapting LLMs for the Medical Domain in Portuguese: A Study on Fine-Tuning and Model Evaluation.

Pedro Henrique Paiola, Gabriel Lino Garcia, João Renato Ribeiro Manesco, Mateus Roder, Douglas Rodrigues, João Paulo Papa

CoRR, 2024

A comprehensive study among distance measures on supervised optimum-path forest classification.

Gustavo H. de Rosa, Mateus Roder, Leandro A. Passos, João Paulo Papa

Appl. Soft Comput., 2024

Convolutional Neural Networks and Image Patches for Lithological Classification of Brazilian Pre-Salt Rocks.

Mateus Roder, Leandro Aparecido Passos, Clayton R. Pereira, João Paulo Papa, Altanir Flores de Mello Junior, Marcelo Fagundes de Rezende, Yaro Moisés Parizek Silva, Alexandre Campane Vidal

Proceedings of the 19th International Joint Conference on Computer Vision, 2024

Facial Point Graphs for Amyotrophic Lateral Sclerosis Identification.

Nícolas Barbosa Gomes, Arissa Yoshida, Mateus Roder, Guilherme Camargo de Oliveira, João Paulo Papa

Proceedings of the 19th International Joint Conference on Computer Vision, 2024

Influence of Pixel Perturbation on eXplainable Artificial Intelligence Methods.

Juliana da Costa Feitosa, Mateus Roder, João Paulo Papa, José Remo Ferreira Brega

Proceedings of the 19th International Joint Conference on Computer Vision, 2024

Assessing Levodopa Effectiveness in Parkison's Disease During Gait Using Electroencephalogram and Machine Learning.

Rafael Gonçalves Pires, Clayton Reginaldo Pereira, Tiago Penedo, João Paulo Papa, Mateus Roder, Fabio Augusto Barbieri

Proceedings of the 31st International Conference on Systems, Signals and Image Processing, 2024

2023

Gait Recognition Based on Deep Learning: A Survey.

Claudio Filipi Gonçalves dos Santos, Diego de Souza Oliveira, Leandro A. Passos, Rafael Gonçalves Pires, Daniel Felipe Silva Santos, Lucas Pascotti Valem, Thierry Pinheiro Moreira, Marcos Cleison S. Santana, Mateus Roder, João Paulo Papa, Danilo Colombo

ACM Comput. Surv., 2023

Multimodal Convolutional Deep Belief Networks for Stroke Classification with Fourier Transform.

Mateus Roder, Nícolas Barbosa Gomes, Arissa Yoshida, João Paulo Papa, Fumie Costen

Proceedings of the 36th SIBGRAPI Conference on Graphics, Patterns and Images, 2023

Facial Point Graphs for Stroke Identification.

Nícolas Barbosa Gomes, Arissa Yoshida, Guilherme Camargo de Oliveira, Mateus Roder, João Paulo Papa

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2023

Feature Selection and Hyperparameter Fine-Tuning in Artificial Neural Networks for Wood Quality Classification.

Mateus Roder, Leandro Aparecido Passos, João Paulo Papa, André Luis Debiaso Rossi

Proceedings of the Intelligent Systems - 12th Brazilian Conference, 2023

2022

Energy-Based Dropout in Restricted Boltzmann Machines: Why Not Go Random.

Mateus Roder, Gustavo Henrique de Rosa, Victor Hugo C. de Albuquerque, André L. D. Rossi, João P. Papa

IEEE Trans. Emerg. Top. Comput. Intell., 2022

Neighbour-based bag-of-samplings for person identification through handwritten dynamics and convolutional neural networks.

Gustavo H. de Rosa, Mateus Roder, João P. Papa

Expert Syst. J. Knowl. Eng., 2022

Comparative Study Between Distance Measures On Supervised Optimum-Path Forest Classification.

Gustavo Henrique de Rosa, Mateus Roder, João Paulo Papa

CoRR, 2022

MaxDropoutV2: An Improved Method to Drop Out Neurons in Convolutional Neural Networks.

Claudio Filipi Goncalves dos Santos, Mateus Roder, Leandro Aparecido Passos, João Paulo Papa

Proceedings of the Pattern Recognition and Image Analysis - 10th Iberian Conference, 2022

2021

Fast Ensemble Learning Using Adversarially-Generated Restricted Boltzmann Machines.

Gustavo Henrique de Rosa, Mateus Roder, João P. Papa

CoRR, 2021

Computer-assisted Parkinson's disease diagnosis using fuzzy optimum- path forest and Restricted Boltzmann Machines.

Renato William R. de Souza, Daniel Santos da Silva, Leandro A. Passos, Mateus Roder, Marcos C. S. Santana, Plácido Rogério Pinheiro, Victor Hugo C. de Albuquerque

Comput. Biol. Medicine, 2021

Reinforcing learning in Deep Belief Networks through nature-inspired optimization.

Mateus Roder, Leandro Aparecido Passos, Gustavo Henrique de Rosa, Victor Hugo C. de Albuquerque, João Paulo Papa

Appl. Soft Comput., 2021

Improving Pre- Trained Weights through Meta - Heuristics Fine- Tuning.

Gustavo Henrique de Rosa, Mateus Roder, João Paulo Papa, Claudio Filipi Goncalves dos Santos

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks.

Mateus Roder, Jurandy Almeida, Gustavo Henrique de Rosa, Leandro A. Passos, André L. D. Rossi, João P. Papa

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Enhancing Shallow Neural Networks Through Fourier-based Information Fusion for Stroke Classification.

Mateus Roder, Gustavo Henrique Rosa, João Paulo Papa, Daniel Carlos Guimarães Pedronette

Proceedings of the 34th SIBGRAPI Conference on Graphics, Patterns and Images, 2021

Fine-Tuning Dropout Regularization in Energy-Based Deep Learning.

Gustavo Henrique de Rosa, Mateus Roder, João P. Papa

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2021

Enhancing Hyper-to-Real Space Projections Through Euclidean Norm Meta-heuristic Optimization.

Luiz Carlos Felix Ribeiro, Mateus Roder, Gustavo Henrique de Rosa, Leandro A. Passos, João P. Papa

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2021

2020

Learnergy: Energy-based Machine Learners.

Mateus Roder, Gustavo Henrique de Rosa, João Paulo Papa

Dataset, September, 2020

On the Assessment of Nature-Inspired Meta-Heuristic Optimization Techniques to Fine-Tune Deep Belief Networks.

Leandro Aparecido Passos, Gustavo Henrique de Rosa, Douglas Rodrigues, Mateus Roder, João Paulo Papa

Proceedings of the Deep Neural Evolution - Deep Learning with Evolutionary Computation, 2020

Learnergy: Energy-based Machine Learners.

Mateus Roder, Gustavo Henrique de Rosa, João Paulo Papa

CoRR, 2020

MaxDropout: Deep Neural Network Regularization Based on Maximum Output Values.

Claudio Filipi Goncalves dos Santos, Danilo Colombo, Mateus Roder, João Paulo Papa

Proceedings of the 25th International Conference on Pattern Recognition, 2020

A Layer-Wise Information Reinforcement Approach to Improve Learning in Deep Belief Networks.

Mateus Roder, Leandro A. Passos, Luiz Carlos Felix Ribeiro, Clayton R. Pereira, João Paulo Papa

Proceedings of the Artificial Intelligence and Soft Computing, 2020

Intestinal Parasites Classification Using Deep Belief Networks.

Mateus Roder, Leandro A. Passos, Luiz Carlos Felix Ribeiro, Barbara Caroline Benato, Alexandre Xavier Falcão, João Paulo Papa

Proceedings of the Artificial Intelligence and Soft Computing, 2020

Harnessing Particle Swarm optimization Through Relativistic Velocity.

Mateus Roder, Gustavo Henrique de Rosa, Leandro Aparecido Passos, João Paulo Papa, André Luis Debiaso Rossi

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

Fine-Tuning Temperatures in Restricted Boltzmann Machines Using Meta-Heuristic Optimization.

Mateus Roder, Gustavo Henrique de Rosa, João Paulo Papa, Fabricio Aparecido Breve

Proceedings of the IEEE Congress on Evolutionary Computation, 2020