104 citations · 132 across the 15 of their papers we have counts for
15 papers
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 +3
This study evaluates the performance of large language models (LLMs) as medical agents in Portuguese, aiming to develop a reliable and relevant virtual assistant for healthcare pro…
Feature Selection and Hyperparameter Fine-tuning in Artificial Neural Networks for Wood Quality Classification
Mateus Roder, Leandro Aparecido Passos, João Paulo Papa +1
Quality classification of wood boards is an essential task in the sawmill industry, which is still usually performed by human operators in small to median companies in developing c…
Facial Point Graphs for Amyotrophic Lateral Sclerosis Identification
Nícolas Barbosa Gomes, Arissa Yoshida, Mateus Roder +2
Identifying Amyotrophic Lateral Sclerosis (ALS) in its early stages is essential for establishing the beginning of treatment, enriching the outlook, and enhancing the overall well-…
Enhancing Hyper-To-Real Space Projections Through Euclidean Norm Meta-Heuristic Optimization
Luiz C. F. Ribeiro, Mateus Roder, Gustavo H. de Rosa +2
The continuous computational power growth in the last decades has made solving several optimization problems significant to humankind a tractable task; however, tackling some of th…
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…
MaxDropoutV2: An Improved Method to Drop out Neurons in Convolutional Neural Networks
Claudio Filipi Goncalves do Santos, Mateus Roder, Leandro A. Passos +1
In the last decade, exponential data growth supplied the machine learning-based algorithms' capacity and enabled their usage in daily life activities. Additionally, such an improve…
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,…
Gait Recognition Based on Deep Learning: A Survey
Claudio Filipi Gonçalves dos Santos, Diego de Souza Oliveira, Leandro A. Passos +8
In general, biometry-based control systems may not rely on individual expected behavior or cooperation to operate appropriately. Instead, such systems should be aware of malicious…
A Layer-Wise Information Reinforcement Approach to Improve Learning in Deep Belief Networks
Mateus Roder, Leandro A. Passos, Luiz Carlos Felix Ribeiro +2
With the advent of deep learning, the number of works proposing new methods or improving existent ones has grown exponentially in the last years. In this scenario, "very deep" mode…
Intestinal Parasites Classification Using Deep Belief Networks
Mateus Roder, Leandro A. Passos, Luiz Carlos Felix Ribeiro +3
Currently, approximately billion people are infected by intestinal parasites worldwide. Diseases caused by such infections constitute a public health problem in most tropical c…
Energy-based Dropout in Restricted Boltzmann Machines: Why not go random
Mateus Roder, Gustavo H. de Rosa, Victor Hugo C. de Albuquerque +2
Deep learning architectures have been widely fostered throughout the last years, being used in a wide range of applications, such as object recognition, image reconstruction, and s…
Fast Ensemble Learning Using Adversarially-Generated Restricted Boltzmann Machines
Gustavo H. de Rosa, Mateus Roder, João P. Papa
Machine Learning has been applied in a wide range of tasks throughout the last years, ranging from image classification to autonomous driving and natural language processing. Restr…
MaxDropout: Deep Neural Network Regularization Based on Maximum Output Values
Claudio Filipi Goncalves do Santos, Danilo Colombo, Mateus Roder +1
Different techniques have emerged in the deep learning scenario, such as Convolutional Neural Networks, Deep Belief Networks, and Long Short-Term Memory Networks, to cite a few. In…
Learnergy: Energy-based Machine Learners
Mateus Roder, Gustavo Henrique de Rosa, João Paulo Papa
Throughout the last years, machine learning techniques have been broadly encouraged in the context of deep learning architectures. An exciting algorithm denoted as Restricted Boltz…