1.1k citations · 2.3k across the 40 of their papers we have counts for
40 papers
Warm-Starting QAOA with XY Mixers: A Novel Approach for Quantum-Enhanced Vehicle Routing Optimization
Rafael S. do Carmo, Marcos C. S. Santana, Felipe F. Fanchini +2
Quantum optimization algorithms, such as the Quantum Approximate Optimization Algorithm, are emerging as promising heuristics for solving complex combinatorial problems. To improve…
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…
Video Segmentation Learning Using Cascade Residual Convolutional Neural Network
Daniel F. S. Santos, Rafael G. Pires, Danilo Colombo +1
Video segmentation consists of a frame-by-frame selection process of meaningful areas related to foreground moving objects. Some applications include traffic monitoring, human trac…
DDIPNet and DDIPNet+: Discriminant Deep Image Prior Networks for Remote Sensing Image Classification
Daniel F. S. Santos, Rafael G. Pires, Leandro A. Passos +1
Research on remote sensing image classification significantly impacts essential human routine tasks such as urban planning and agriculture. Nowadays, the rapid advance in technolog…
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…
FEMa-FS: Finite Element Machines for Feature Selection
Lucas Biaggi, João P. Papa, Kelton A. P Costa +2
Identifying anomalies has become one of the primary strategies towards security and protection procedures in computer networks. In this context, machine learning-based methods emer…
PL-kNN: A Parameterless Nearest Neighbors Classifier
Danilo Samuel Jodas, Leandro Aparecido Passos, Ahsan Adeel +1
Demands for minimum parameter setup in machine learning models are desirable to avoid time-consuming optimization processes. The -Nearest Neighbors is one of the most effective…
ComplexWoundDB: A Database for Automatic Complex Wound Tissue Categorization
Talita A. Pereira, Regina C. Popim, Leandro A. Passos +3
Complex wounds usually face partial or total loss of skin thickness, healing by secondary intention. They can be acute or chronic, figuring infections, ischemia and tissue necrosis…
Canonical Cortical Graph Neural Networks and its Application for Speech Enhancement in Audio-Visual Hearing Aids
Leandro A. Passos, João Paulo Papa, Amir Hussain +1
Despite the recent success of machine learning algorithms, most models face drawbacks when considering more complex tasks requiring interaction between different sources, such as m…
A Novel Approach for Optimum-Path Forest Classification Using Fuzzy Logic
Renato W. R. de Souza, João V. C. de Oliveira, Leandro A. Passos +3
In the past decades, fuzzy logic has played an essential role in many research areas. Alongside, graph-based pattern recognition has shown to be of great importance due to its flex…
An End-to-End Approach for Seam Carving Detection using Deep Neural Networks
Thierry P. Moreira, Marcos Cleison S. Santana, Leandro A. Passos João Paulo Papa +1
Seam carving is a computational method capable of resizing images for both reduction and expansion based on its content, instead of the image geometry. Although the technique is mo…
Handling Imbalanced Datasets Through Optimum-Path Forest
Leandro Aparecido Passos, Danilo S. Jodas, Luiz C. F. Ribeiro +3
In the last decade, machine learning-based approaches became capable of performing a wide range of complex tasks sometimes better than humans, demanding a fraction of the time. Suc…
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,…
A Review of Deep Learning-based Approaches for Deepfake Content Detection
Leandro A. Passos, Danilo Jodas, Kelton A. P. da Costa +5
Recent advancements in deep learning generative models have raised concerns as they can create highly convincing counterfeit images and videos. This poses a threat to people's inte…
Modeling Implicit Bias with Fuzzy Cognitive Maps
Gonzalo Nápoles, Isel Grau, Leonardo Concepción +2
This paper presents a Fuzzy Cognitive Map model to quantify implicit bias in structured datasets where features can be numeric or discrete. In our proposal, problem features are ma…
Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks
Claudio Filipi Gonçalves dos Santos, João Paulo Papa
Several image processing tasks, such as image classification and object detection, have been significantly improved using Convolutional Neural Networks (CNN). Like ResNet and Effic…
Improving Transferability of Domain Adaptation Networks Through Domain Alignment Layers
Lucas Fernando Alvarenga e Silva, Daniel Carlos Guimarães Pedronette, Fábio Augusto Faria +2
Deep learning (DL) has been the primary approach used in various computer vision tasks due to its relevant results achieved on many tasks. However, on real-world scenarios with par…
Speeding Up OPFython with Numba
Gustavo H. de Rosa, João Paulo Papa
A graph-inspired classifier, known as Optimum-Path Forest (OPF), has proven to be a state-of-the-art algorithm comparable to Logistic Regressors, Support Vector Machines in a wide…
Hierarchical Learning Using Deep Optimum-Path Forest
Luis C. S. Afonso, Clayton R. Pereira, Silke A. T. Weber +3
Bag-of-Visual Words (BoVW) and deep learning techniques have been widely used in several domains, which include computer-assisted medical diagnoses. In this work, we are interested…
Information Ranking Using Optimum-Path Forest
Nathalia Q. Ascenção, Luis C. S. Afonso, Danilo Colombo +2
The task of learning to rank has been widely studied by the machine learning community, mainly due to its use and great importance in information retrieval, data mining, and natura…
Image Denoising using Attention-Residual Convolutional Neural Networks
Rafael G. Pires, Daniel F. S. Santos, Marcos C. S. Santana +2
During the image acquisition process, noise is usually added to the data mainly due to physical limitations of the acquisition sensor, and also regarding imprecisions during the da…
Learning Visual Representations with Optimum-Path Forest and its Applications to Barrett's Esophagus and Adenocarcinoma Diagnosis
Luis A. de Souza, Luis C. S. Afonso, Alanna Ebigbo +5
In this work, we introduce the unsupervised Optimum-Path Forest (OPF) classifier for learning visual dictionaries in the context of Barrett's esophagus (BE) and automatic adenocarc…
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…