Mateus Roder

Orcid: 0000-0002-3112-5290

According to our database1, Mateus Roder authored at least 26 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Convolutional Neural Networks and Image Patches for Lithological Classification of Brazilian Pre-Salt Rocks.
Proceedings of the 19th International Joint Conference on Computer Vision, 2024

Facial Point Graphs for Amyotrophic Lateral Sclerosis Identification.
Proceedings of the 19th International Joint Conference on Computer Vision, 2024

Influence of Pixel Perturbation on eXplainable Artificial Intelligence Methods.
Proceedings of the 19th International Joint Conference on Computer Vision, 2024

2023
Gait Recognition Based on Deep Learning: A Survey.
ACM Comput. Surv., 2023

Multimodal Convolutional Deep Belief Networks for Stroke Classification with Fourier Transform.
Proceedings of the 36th SIBGRAPI Conference on Graphics, Patterns and Images, 2023

Facial Point Graphs for Stroke Identification.
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.
Proceedings of the Intelligent Systems - 12th Brazilian Conference, 2023

2022
Energy-Based Dropout in Restricted Boltzmann Machines: Why Not Go Random.
IEEE Trans. Emerg. Top. Comput. Intell., 2022

Neighbour-based bag-of-samplings for person identification through handwritten dynamics and convolutional neural networks.
Expert Syst. J. Knowl. Eng., 2022

Comparative Study Between Distance Measures On Supervised Optimum-Path Forest Classification.
CoRR, 2022

MaxDropoutV2: An Improved Method to Drop Out Neurons in Convolutional Neural Networks.
Proceedings of the Pattern Recognition and Image Analysis - 10th Iberian Conference, 2022

2021
Fast Ensemble Learning Using Adversarially-Generated Restricted Boltzmann Machines.
CoRR, 2021

Computer-assisted Parkinson's disease diagnosis using fuzzy optimum- path forest and Restricted Boltzmann Machines.
Comput. Biol. Medicine, 2021

Reinforcing learning in Deep Belief Networks through nature-inspired optimization.
Appl. Soft Comput., 2021

Improving Pre- Trained Weights through Meta - Heuristics Fine- Tuning.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Enhancing Shallow Neural Networks Through Fourier-based Information Fusion for Stroke Classification.
Proceedings of the 34th SIBGRAPI Conference on Graphics, Patterns and Images, 2021

Fine-Tuning Dropout Regularization in Energy-Based Deep Learning.
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.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2021

2020
On the Assessment of Nature-Inspired Meta-Heuristic Optimization Techniques to Fine-Tune Deep Belief Networks.
Proceedings of the Deep Neural Evolution - Deep Learning with Evolutionary Computation, 2020

Learnergy: Energy-based Machine Learners.
CoRR, 2020

MaxDropout: Deep Neural Network Regularization Based on Maximum Output Values.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

A Layer-Wise Information Reinforcement Approach to Improve Learning in Deep Belief Networks.
Proceedings of the Artificial Intelligence and Soft Computing, 2020

Intestinal Parasites Classification Using Deep Belief Networks.
Proceedings of the Artificial Intelligence and Soft Computing, 2020

Harnessing Particle Swarm optimization Through Relativistic Velocity.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

Fine-Tuning Temperatures in Restricted Boltzmann Machines Using Meta-Heuristic Optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020


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