Saulo Moraes Villela

Orcid: 0000-0001-5958-4766

According to our database1, Saulo Moraes Villela authored at least 30 papers between 2015 and 2024.

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

Timeline

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Bibliography

2024
Composite loss function for 3-D poststack seismic data compression.
Comput. Geosci., 2024

2023
Mapping user behaviors to identify professional accounts in Ethereum using semi-supervised learning.
Expert Syst. Appl., November, 2023

Graph Cuts and Deep Neural Networks for Fire Detection.
Proceedings of the 36th SIBGRAPI Conference on Graphics, Patterns and Images, 2023

2022
Poststack Seismic Data Compression Using a Generative Adversarial Network.
IEEE Geosci. Remote. Sens. Lett., 2022

Analysis of account behaviors in Ethereum during an economic impact event.
CoRR, 2022

Previsão da Classe de Frequência de Acesso de Objetos em Serviços de Armazenamento em Nuvem.
Proceedings of the 40th Brazilian Symposium on Computer Networks and Distributed Systems, 2022

Procedural Content Generation using Reinforcement Learning and Entropy Measure as Feedback.
Proceedings of the 21st Brazilian Symposium on Computer Games and Digital Entertainment, 2022

Combining Neural Networks and a Color Classifier for Fire Detection.
Proceedings of the Intelligent Systems - 11th Brazilian Conference, 2022

2021
Fighting Under-price DoS Attack in Ethereum with Machine Learning Techniques.
SIGMETRICS Perform. Evaluation Rev., 2021

Analyzing Transaction Confirmation in Ethereum Using Machine Learning Techniques.
SIGMETRICS Perform. Evaluation Rev., 2021

Weighted voting of multi-stream convolutional neural networks for video-based action recognition using optical flow rhythms.
J. Vis. Commun. Image Represent., 2021

An analysis of the fees and pending time correlation in Ethereum.
Int. J. Netw. Manag., 2021

An ordered search with a large margin classifier for feature selection.
Appl. Soft Comput., 2021

Improving the one-against-all binary approach for multiclass classification using balancing techniques.
Appl. Intell., 2021

Identifying User Behavior Profiles in Ethereum Using Machine Learning Techniques.
Proceedings of the 2021 IEEE International Conference on Blockchain, 2021

2020
Large margin classifiers to generate synthetic data for imbalanced datasets.
Appl. Intell., 2020

Multi-stream Architecture with Symmetric Extended Visual Rhythms for Deep Learning Human Action Recognition.
Proceedings of the 15th International Joint Conference on Computer Vision, 2020

Filter Learning from Deep Descriptors of a Fully Convolutional Siamese Network for Tracking in Videos.
Proceedings of the 15th International Joint Conference on Computer Vision, 2020

An Evolutionary Analytic Center Classifier.
Proceedings of the Intelligent Systems - 9th Brazilian Conference, 2020

2019
Ufjf-Mltk: a framework for machine learning algorithms.
Proceedings of the XV Brazilian Symposium on Information Systems, 2019

Learnable Visual Rhythms Based on the Stacking of Convolutional Neural Networks for Action Recognition.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Human Action Recognition Using Convolutional Neural Networks with Symmetric Time Extension of Visual Rhythms.
Proceedings of the Computational Science and Its Applications - ICCSA 2019, 2019

A best-first branch-and-bound search for solving the transductive inference problem using support vector machines.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

An Ordered Search for Subset Selection in Support Vector Orthogonal Regression.
Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019

2018
An Approximative Bayes-Optimal Kernel Classifier Based on Version Space Reduction.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Metaheuristics in the Project of Cellular Automata for Key Generation in Stream Cipher Algorithms.
Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

2016
Incremental p-margin algorithm for classification with arbitrary norm.
Pattern Recognit., 2016

Version Space Reduction Based on Ensembles of Dissimilar Balanced Perceptrons.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015
Feature Selection from Microarray Data via an Ordered Search with Projected Margin.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

A Novel Ensemble Approach Based on Balanced Perceptrons Applied to Microarray Datasets.
Proceedings of the 2015 Brazilian Conference on Intelligent Systems, 2015


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