131 citations · 319 across the 16 of their papers we have counts for
6 papers · 1 filter
A survey on text generation using generative adversarial networks
Gustavo Henrique de Rosa, João Paulo Papa
This work presents a thorough review concerning recent studies and text generation advancements using Generative Adversarial Networks. The usage of adversarial learning for text ge…
Improving Pre-Trained Weights Through Meta-Heuristics Fine-Tuning
Gustavo H. de Rosa, Mateus Roder, João Paulo Papa +1
Machine Learning algorithms have been extensively researched throughout the last decade, leading to unprecedented advances in a broad range of applications, such as image classific…
From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks
Mateus Roder, Jurandy Almeida, Gustavo H. de Rosa +3
In the last decade, exponential data growth supplied machine learning-based algorithms' capacity and enabled their usage in daily-life activities. Additionally, such an improvement…
Robust deep learning for eye fundus images: Bridging real and synthetic data for enhancing generalization
Guilherme C. Oliveira, Gustavo H. Rosa, Daniel C. G. Pedronette +4
Deep learning applications for assessing medical images are limited because the datasets are often small and imbalanced. The use of synthetic data has been proposed in the literatu…
LiteTransformerSearch: Training-free Neural Architecture Search for Efficient Language Models
Mojan Javaheripi, Gustavo H. de Rosa, Subhabrata Mukherjee +6
The Transformer architecture is ubiquitously used as the building block of large-scale autoregressive language models. However, finding architectures with the optimal trade-off bet…
Comparative Study Between Distance Measures On Supervised Optimum-Path Forest Classification
Gustavo Henrique de Rosa, Mateus Roder, João Paulo Papa
Machine Learning has attracted considerable attention throughout the past decade due to its potential to solve far-reaching tasks, such as image classification, object recognition,…