Table of Contents

• Transformer Model for Fault Detection from Brazilian Pre-salt Seismic DataLeticia da Silva Bomfim, Oton Cunha, Michelle Kuroda, Alexandre Campane Vidal, Hélio Pedrini. 3-17 [doi]
• Evaluating Recent Legal Rhetorical Role Labeling Approaches Supported by Transformer EncodersAlexandre Gomes de Lima, José G. Moreno 0001, Taoufiq Dkaki, Eduardo Henrique da S. Aranha, Mohand Boughanem. 18-32 [doi]
• Dog Face Recognition Using Vision TransformerVictor Hugo Braguim Canto, João Renato Ribeiro Manesco, Gustavo Botelho de Souza, Aparecido Nilceu Marana. 33-47 [doi]
• Convolutional Neural Networks for the Molecular Detection of COVID-19Anisio P. Santos, Anage C. Mundim Filho, Robinson Sabino-Silva, Murillo G. Carneiro. 51-62 [doi]
• Hierarchical Graph Convolutional Networks for Image ClassificationJoão Pedro Oliveira Batisteli, Silvio Jamil Ferzoli Guimarães, Zenilton Kleber Gonçalves do Patrocínio Jr.. 63-76 [doi]
• Interpreting Convolutional Neural Networks for Brain Tumor Classification: An Explainable Artificial Intelligence ApproachDieine Estela Bernieri Schiavon, Carla Diniz Lopes Becker, Viviane Rodrigues Botelho, Thatiane Alves Pianoski. 77-91 [doi]
• Enhancing Stock Market Predictions Through the Integration of Convolutional and Recursive LSTM Blocks: A Cross-market AnalysisFilipe Ramos, Guilherme Silva 0006, Eduardo Luz 0001, Pedro Silva 0004. 92-106 [doi]
• Ensemble Architectures and Efficient Fusion Techniques for Convolutional Neural Networks: An Analysis on Resource Optimization StrategiesCicero L. Costa, Danielli A. Lima, Célia A. Zorzo Barcelos, Bruno A. N. Travençolo. 107-121 [doi]
• Dog Face Recognition Using Deep Features EmbeddingsJoão P. B. Andrade, Leonardo Ferreira da Costa, Lucas S. Fernandes, Paulo A. L. Rego, José G. R. Maia. 125-139 [doi]
• Clinical Oncology Textual Notes Analysis Using Machine Learning and Deep LearningDiego Pinheiro da Silva, William da Rosa Fröhlich, Marco Antônio Schwertner, Sandro José Rigo. 140-153 [doi]
• EfficientDeepLab for Automated Trachea Segmentation on Medical ImagesArthur Guilherme Santos Fernandes, Geraldo Braz Junior, João Otávio Bandeira Diniz, Aristófanes Corrêa Silva, Caio Eduardo Falcõ Matos. 154-166 [doi]
• Multi-label Classification of Pathologies in Chest Radiograph Images Using DenseNetAlison Corrêa Mendes, Alexandre César Pinto Pessoa 0001, Anselmo Cardoso de Paiva. 167-180 [doi]
• Does Pre-training on Brain-Related Tasks Results in Better Deep-Learning-Based Brain Age Biomarkers?Bruno Machado Pacheco, Victor Hugo Rocha de Oliveira, Augusto Braga Fernandes Antunes, Saulo Domingos de Souza Pedro, Danilo Silva. 181-194 [doi]
• Applying Reinforcement Learning for Multiple Functions in Swarm IntelligenceAndré A. V. Escorel Ribeiro, Rodrigo Cesar Lira, Mariana Macedo, Hugo Valadares Siqueira, Carmelo J. A. Bastos Filho. 197-212 [doi]
• Deep Reinforcement Learning for Voltage Control in Power SystemsMauricio W. Barg, Barbara S. Rodrigues, Gabriela Teixeira Justino, Kleyton Pontes Cotta, Hugo R. V. Portuita, Flávio L. Loução Jr., Iran Pereira Abreu, Antonio C. P. Brasil Jr.. 213-227 [doi]
• Performance Analysis of Generative Adversarial Networks and Diffusion Models for Face AgingBruno Kemmer, Rodolfo Simões, Victor Ivamoto, Clodoaldo Ap. M. Lima. 228-242 [doi]
• Occluded Face In-painting Using Generative Adversarial Networks - A ReviewVictor Ivamoto, Rodolfo Simões, Bruno Kemmer, Clodoaldo Ap. M. Lima. 243-258 [doi]
• Classification of Facial Images to Assist in the Diagnosis of Autism Spectrum Disorder: A Study on the Effect of Face Detection and Landmark Identification AlgorithmsGabriel C. Michelassi, Henrique S. Bortoletti, Tuany D. Pinheiro, Thiago Nobayashi, Fabio R. D. de Barros, Rafael Luiz Testa, Andréia F. Silva, Mirian C. Revers, Joana Portolese, Hélio Pedrini, Helena Paula Brentani, Fátima L. S. Nunes, Ariane Machado-Lima. 261-275 [doi]
• Constructive Machine Learning and Hierarchical Multi-label Classification for Molecules DesignRodney Renato de Souza Silva, Ricardo Cerri. 276-290 [doi]
• AutoMMLC: An Automated and Multi-objective Method for Multi-label ClassificationAline Marques Del Valle, Rafael Gomes Mantovani, Ricardo Cerri. 291-306 [doi]
• Merging Traditional Feature Extraction and Deep Learning for Enhanced Hop Variety Classification: A Comparative Study Using the UFOP-HVD DatasetPedro Henrique Nascimento Castro, Gabriel Cássia Fortuna, Pedro Silva 0004, Andrea G. C. Bianchi, Gladston Moreira, Eduardo José da S. Luz. 307-322 [doi]
• Feature Selection and Hyperparameter Fine-Tuning in Artificial Neural Networks for Wood Quality ClassificationMateus Roder, Leandro Aparecido Passos, João Paulo Papa, André Luis Debiaso Rossi. 323-337 [doi]
• A Feature-Based Out-of-Distribution Detection Approach in Skin Lesion ClassificationThiago M. Carvalho, Marley M. B. R. Vellasco, José F. M. do Amaral, Karla Figueiredo. 338-352 [doi]
• A Framework for Characterizing What Makes an Instance Hard to ClassifyMaria Gabriela Valeriano, Pedro Yuri Arbs Paiva, Carlos Roberto Veiga Kiffer, Ana Carolina Lorena. 353-367 [doi]
• Physicochemical Properties for Promoter ClassificationLauro Moraes, Eduardo José da S. Luz, Gladston Moreira. 368-382 [doi]
• Critical Analysis of AI Indicators in Terms of Weighting and Aggregation ApproachesRenata Pelissari, Betania Silva Carneiro Campello, Guilherme Dean Pelegrina, Ricardo Suyama, Leonardo Tomazeli Duarte. 385-399 [doi]
• Estimating Code Running Time Complexity with Machine LearningRicardo J. Pfitscher, Gabriel B. Rodenbusch, Anderson Dias, Paulo Vieira, Nuno M. M. D. Fouto. 400-414 [doi]
• The Effect of Statistical Hypothesis Testing on Machine Learning Model SelectionMarcel Chacon Gonçalves, Rodrigo C. P. Silva. 415-427 [doi]