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Erikson Júlio De Aguiar
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2020 – today
- 2024
- [c6]Erikson Júlio De Aguiar, Caetano Traina, Agma J. M. Traina:
RADAR-MIX: How to Uncover Adversarial Attacks in Medical Image Analysis through Explainability. CBMS 2024: 436-441 - 2023
- [c5]Erikson Júlio De Aguiar, Márcus V. L. Costa
, Caetano Traina
Assessing Vulnerabilities of Deep Learning Explainability in Medical Image Analysis Under Adversarial Settings. CBMS 2023: 13-16 - [c4]Márcus V. L. Costa
A Deep Learning-based Radiomics Approach for COVID-19 Detection from CXR Images using Ensemble Learning Model. CBMS 2023: 517-522 - 2022
- [j2]Erikson Júlio De Aguiar
A blockchain-based protocol for tracking user access to shared medical imaging. Future Gener. Comput. Syst. 134: 348-360 (2022) - [c3]Jonathan S. Ramos, Erikson Júlio De Aguiar, Ivar Vargas Belizario
Analysis of vertebrae without fracture on spine MRI to assess bone fragility: A Comparison of Traditional Machine Learning and Deep Learning. CBMS 2022: 78-83 - [c2]Erikson Júlio De Aguiar, Karem D. Marcomini, Felipe A. Quirino, Marco A. Gutierrez
Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases. Computer-Aided Diagnosis 2022 - 2021
- [j1]Erikson Júlio De Aguiar
A Survey of Blockchain-Based Strategies for Healthcare. ACM Comput. Surv. 53(2): 27:1-27:27 (2021)
2010 – 2019
- 2018
- [c1]Erikson Júlio De Aguiar, Bruno S. Faiçal, Jó Ueyama, Glauco Carlos Silva, André Luís Andrade Menolli:
Análise de Sentimento em Redes Sociais para a Língua Portuguesa Utilizando Algoritmos de Classificação. SBRC 2018: 393-406
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last updated on 2024-11-28 20:33 CET by the dblp team
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