Gustavo H. Rosa

Orcid: 0000-0002-6442-8343

According to our database1, Gustavo H. Rosa authored at least 57 papers between 2012 and 2024.

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Bibliography

2024
Robust deep learning for eye fundus images: Bridging real and synthetic data for enhancing generalization.
Biomed. Signal Process. Control., 2024

A comprehensive study among distance measures on supervised optimum-path forest classification.
Appl. Soft Comput., 2024

2023
Fine-Tuning Restricted Boltzmann Machines Using No-Boundary Jellyfish.
Proceedings of the 18th International Joint Conference on Computer Vision, 2023

Small Character Models Match Large Word Models for Autocomplete Under Memory Constraints.
Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing, 2023

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

Convolutional neural networks ensembles through single-iteration optimization.
Soft Comput., 2022

Optimum-path forest stacking-based ensemble for intrusion detection.
Evol. Intell., 2022

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

Which Generative Adversarial Network Yields High-Quality Synthetic Medical Images: Investigation Using AMD Image Datasets.
CoRR, 2022

LiteTransformerSearch: Training-free On-device Search for Efficient Autoregressive Language Models.
CoRR, 2022

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

Deep Learning-Based Abstractive Summarization for Brazilian Portuguese Texts.
Proceedings of the Intelligent Systems - 11th Brazilian Conference, 2022

2021
OPFython: A Python implementation for Optimum-Path Forest.
Softw. Impacts, 2021

A survey on text generation using generative adversarial networks.
Pattern Recognit., 2021

Speeding Up OPFython with Numba.
CoRR, 2021

Fast Ensemble Learning Using Adversarially-Generated Restricted Boltzmann Machines.
CoRR, 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
Opytimizer: A Nature-Inspired Python Optimizer.
Dataset, December, 2020

OPFython: A Python-Inspired Optimum-Path Forest Classifier.
Dataset, September, 2020

Learnergy: Energy-based Machine Learners.
Dataset, September, 2020

Adaptive Improved Flower Pollination Algorithm for Global Optimization.
Proceedings of the Nature-Inspired Computation in Data Mining and Machine Learning, 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

OPFython: A Python-Inspired Optimum-Path Forest Classifier.
CoRR, 2020

A nature-inspired feature selection approach based on hypercomplex information.
Appl. Soft Comput., 2020

Creating Classifier Ensembles through Meta-heuristic Algorithms for Aerial Scene Classification.
Proceedings of the 25th International Conference on Pattern Recognition, 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

2019
Opytimizer: A Nature-Inspired Python Optimizer.
Dataset, December, 2019

Semi-supervised learning with connectivity-driven convolutional neural networks.
Pattern Recognit. Lett., 2019

Fine-tuning restricted Boltzmann machines using quaternions and its application for spam detection.
IET Networks, 2019

A recurrence plot-based approach for Parkinson's disease identification.
Future Gener. Comput. Syst., 2019

Opytimizer: A Nature-Inspired Python Optimizer.
CoRR, 2019

2018
Handling dropout probability estimation in convolution neural networks using meta-heuristics.
Soft Comput., 2018

Feature selection through binary brain storm optimization.
Comput. Electr. Eng., 2018

Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification.
Artif. Intell. Medicine, 2018

Stroke Lesion Detection Using Convolutional Neural Networks.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Environmental Monitoring Using Drone Images and Convolutional Neural Networks.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
A binary-constrained Geometric Semantic Genetic Programming for feature selection purposes.
Pattern Recognit. Lett., 2017

LibOPT: An Open-Source Platform for Fast Prototyping Soft Optimization Techniques.
CoRR, 2017

Quaternion-based Deep Belief Networks fine-tuning.
Appl. Soft Comput., 2017

Feature selection using geometric semantic genetic programming.
Proceedings of the Genetic and Evolutionary Computation Conference, 2017

Quaternionic Flower Pollination Algorithm.
Proceedings of the Computer Analysis of Images and Patterns, 2017

2016
Convolutional Neural Networks Applied for Parkinson's Disease Identification.
Proceedings of the Machine Learning for Health Informatics, 2016

Deep Learning-Aided Parkinson's Disease Diagnosis from Handwritten Dynamics.
Proceedings of the 29th SIBGRAPI Conference on Graphics, Patterns and Images, 2016

Learning Parameters in Deep Belief Networks Through Firefly Algorithm.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2016

2015
Model selection for Discriminative Restricted Boltzmann Machines through meta-heuristic techniques.
J. Comput. Sci., 2015

Malware Detection in Android-Based Mobile Environments Using Optimum-Path Forest.
Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

On the Model Selection of Bernoulli Restricted Boltzmann Machines Through Harmony Search.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Fine-Tuning Convolutional Neural Networks Using Harmony Search.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2015

2014
On the Training of Artificial Neural Networks with Radial Basis Function Using Optimum-Path Forest Clustering.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014

2012
Automatic landslide recognition through Optimum-Path Forest.
Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012


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