Aqui você encontra referências para as publicações de nossos pesquisadores em revistas especializadas e anais de eventos científicos.
Artigos em periódicos
1. R. P. Ederli, D. Vega-Oliveros, A. Soriano-Vargas, A. Rocha and Z. Dias, “Sleep-Wake Classification using Recurrence Plots from Smartwatch Accelerometer Data,” 2023 IEEE Latin American Conference on Computational Intelligence (LA-CCI), Recife-Pe, Brazil, 2023, pp. 1-6. (DOI: 10.1109/LA-CCI58595.2023.10409374).
2. P. H. Barros, J. C. Guevara, L. Villas, D. Guidoni, N. L. S. da Fonseca and H. S. Ramos, “A Novel Federated Meta-Learning Approach for Discriminating Sedentary Behavior From Wearable Data,” in IEEE Internet of Things Journal. (DOI: 10.1109/JIOT.2024.3420891).
Publicações em conferências
1. P. H. Barros and H. S. Ramos, “A novel aggregation method to promote safety security for poisoning attacks in Federated Learning,” GLOBECOM 2022 – 2022 IEEE Global Communications Conference, Rio de Janeiro, Brazil, 2022, pp. 3869-3874. (DOI: 10.1109/GLOBECOM48099.2022.10001680).
2. J. Jorge et al., “Applying Federated Learning in the detection of Freezing of Gait in Parkinson’s disease,” 2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC), Vancouver, WA, USA, 2022, pp. 195-200. (DOI: 10.1109/UCC56403.2022.00037).
3. R. C. Ito and F. J. Von Zuben, “OFA2: A Multi-Objective Perspective for the Once-for-All Neural Architecture Search,” 2023 International Joint Conference on Neural Networks (IJCNN), Gold Coast, Australia, 2023, pp. 1-9. (DOI: 10.1109/IJCNN54540.2023.10191589).
4. Barros, P. H., Guevara, J. C., Villas, L. A., Guidoni, D. L., da Fonseca, N. L. S., & Ramos Filho, H. S. (2024). “Hierarchical Federated Learning Based on Ordinal Patterns for Detecting Sedentary Behavior,” 2024 International Joint Conference on Neural Networks (IJCNN). Yokohama, Japan, 2024.
5. J. Jorge, J. C. Guevara, D. L. Guidoni, H. S. Ramos, L. A. Villas and N. L. S. Da Fonseca, “Tremor Detection in Parkinson’s Disease from Wearable Data: A Comparative Study of Centralized Learning versus Federated Learning,” 2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), Abu Dhabi, United Arab Emirates, 2024, pp. 724-731.
6. P. H. Barros and H. S. Ramos, “A novel aggregation method to promote safety security for poisoning attacks in Federated Learning,” GLOBECOM 2022 – 2022 IEEE Global Communications Conference, Rio de Janeiro, Brazil, 2022, pp. 3869-3874, doi: 10.1109/GLOBECOM48099.2022.10001680.
7. J. Jorge et al., “Applying Federated Learning in the Detection of Freezing of Gait in Parkinson’s Disease,” 2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC), Vancouver, WA, USA, 2022, pp. 195-200. (DOI: 10.1109/UCC56403.2022.00037).