Erikson Júlio De Aguiar

11 papers B 6Journal 3Unranked 2
YearRankTypeTitle / Venue / Authors
2025 B conf
AI-Driven Public Health Surveillance: Analyzing Vulnerable Areas in Brazil Using Remote Sensing and Socioeconomic Data.
CBMS
Joao Pedro Silva, Erikson Júlio De Aguiar, Gabriel Spadon, Agma J. M. Traina, Jose F. Rodrigues
2025 J jnl
DEELE-Rad: exploiting deep radiomics features in deep learning models using COVID-19 chest X-ray images.
Health Inf. Sci. Syst.
Márcus V. L. Costa, Erikson Júlio De Aguiar, Lucas Santiago Rodrigues, Caetano Traina, Agma J. M. Traina
2024 B conf
MedTimeSplit: Continual dataset partitioning to mimic real-world settings for federated learning on Non-IID medical image data.
IEEE Big Data
Erikson Júlio De Aguiar, Agma J. M. Traina, Sumi Helal
2024 B conf
RADAR-MIX: How to Uncover Adversarial Attacks in Medical Image Analysis through Explainability.
CBMS
Erikson Júlio De Aguiar, Caetano Traina, Agma J. M. Traina
2023 B conf
A Deep Learning-based Radiomics Approach for COVID-19 Detection from CXR Images using Ensemble Learning Model.
CBMS
Márcus V. L. Costa, Erikson Júlio De Aguiar, Lucas Santiago Rodrigues, Jonathan S. Ramos, Caetano Traina, Agma J. M. Traina
2023 B conf
Assessing Vulnerabilities of Deep Learning Explainability in Medical Image Analysis Under Adversarial Settings.
CBMS
Erikson Júlio De Aguiar, Márcus V. L. Costa, Caetano Traina, Agma J. M. Traina
2022 J jnl
A blockchain-based protocol for tracking user access to shared medical imaging.
Future Gener. Comput. Syst.
Erikson Júlio De Aguiar, Alyson de Jesus dos Santos, Rodolfo I. Meneguette, Robson E. De Grande, Jó Ueyama
2022 B conf
Analysis of vertebrae without fracture on spine MRI to assess bone fragility: A Comparison of Traditional Machine Learning and Deep Learning.
CBMS
Jonathan S. Ramos, Erikson Júlio De Aguiar, Ivar Vargas Belizario, Márcus V. L. Costa, Jamilly G. Maciel, Mirela T. Cazzolato, Caetano Traina, Marcello H. Nogueira-Barbosa, Agma J. M. Traina
2022 — conf
Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases.
Computer-Aided Diagnosis
Erikson Júlio De Aguiar, Karem D. Marcomini, Felipe A. Quirino, Marco A. Gutierrez, Caetano Traina Jr., Agma J. M. Traina
2021 J jnl
A Survey of Blockchain-Based Strategies for Healthcare.
ACM Comput. Surv.
Erikson Júlio De Aguiar, Bruno S. Faiçal, Bhaskar Krishnamachari, Jó Ueyama
2018 — conf
Análise de Sentimento em Redes Sociais para a Língua Portuguesa Utilizando Algoritmos de Classificação.
SBRC
Erikson Júlio De Aguiar, Bruno S. Faiçal, Jó Ueyama, Glauco Carlos Silva, André Luís Andrade Menolli