Zobrazeno 1 - 10 of 3 665 pro vyhledávání: '"Devilliers"'
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Akademický článek
Curriculum Learning-Based Multivariate Time Series Anomaly Detection
Autor: Devilliers C Dube, Mehmet Akar
Publikováno v: Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 35, Iss 1, Pp 193-https://youtu.be/LiBC6LHn6H8 (2024)
Anomaly detection in multivariate time series (MVTS) is a significant research domain across several industries, including cybersecurity and industrial systems. There have been several deep learning-based methods proposed within this research domain.
Externí odkaz: https://doaj.org/article/e859191ae37843148f597bbf502febc2
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4
Report
Evaluation of Interpretability for Deep Learning algorithms in EEG Emotion Recognition: A case study in Autism
Autor: Mayor-Torres, Juan Manuel, Medina-DeVilliers, Sara, Clarkson, Tessa, Lerner, Matthew D., Riccardi, Giuseppe
Current models on Explainable Artificial Intelligence (XAI) have shown an evident and quantified lack of reliability for measuring feature-relevance when statistically entangled features are proposed for training deep classifiers. There has been an i
Externí odkaz: http://arxiv.org/abs/2111.13208
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9
Report
Interpretable SincNet-based Deep Learning for Emotion Recognition from EEG brain activity
Autor: Mayor-Torres, Juan Manuel, Ravanelli, Mirco, Medina-DeVilliers, Sara E., Lerner, Matthew D., Riccardi, Giuseppe
Machine learning methods, such as deep learning, show promising results in the medical domain. However, the lack of interpretability of these algorithms may hinder their applicability to medical decision support systems. This paper studies an interpr
Externí odkaz: http://arxiv.org/abs/2107.10790
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