Fernando Moncada Martins
Orcid: 0000-0002-6652-9287Affiliations:
- University of Oviedo, Gijón, Spain
According to our database1,
Fernando Moncada Martins authored at least 12 papers
between 2021 and 2026.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2026
Log. J. IGPL, 2026
Early Detection of Neurotoxicity in Neuronal Cultures via Unsupervised Anomaly Detection on MEA Spike Waveforms.
Proceedings of the Hybrid Artificial Intelligent Systems - 21st International Conference, 2026
2025
Inception networks, data augmentation and transfer learning in EEG-based photosensitivity diagnosis.
Mach. Learn. Sci. Technol., 2025
Learning from Normal Brain Activity for Automatic Detection of Photoparoxysmal Responses as Electroencephalogram Anomalies.
Proceedings of the Hybrid Artificial Intelligent Systems - 20th International Conference, 2025
2024
Proceedings of the 19th International Conference on Soft Computing Models in Industrial and Environmental Applications SOCO 2024, 2024
Batch-Balancing Improvement with Data Augmentation Techniques for Clinical Electroencephalographic Data.
Proceedings of the Hybrid Artificial Intelligent Systems - 19th International Conference, 2024
2023
Virtual reality and machine learning in the automatic photoparoxysmal response detection.
Neural Comput. Appl., March, 2023
Data Augmentation Effects on Highly Imbalanced EEG Datasets for Automatic Detection of Photoparoxysmal Responses.
Sensors, February, 2023
Analysis of Frequency Bands in Electroencephalograms for Automatic Detection of Photoparoxysmal Responses.
Proceedings of the Hybrid Artificial Intelligent Systems - 18th International Conference, 2023
2022
A Comparison of Machine Learning Techniques for the Detection of Type-4 PhotoParoxysmal Responses in Electroencephalographic Signals.
Proceedings of the Hybrid Artificial Intelligent Systems - 17th International Conference, 2022
2021
Proceedings of the Hybrid Artificial Intelligent Systems - 16th International Conference, 2021
A Preliminary Study on Automatic Detection and Filtering of Artifacts from EEG Signals.
Proceedings of the 34th IEEE International Symposium on Computer-Based Medical Systems, 2021