Andrea Apicella

Proceedings of the Ital-IA Intelligenza Artificiale, 2024

Improving the Performance of Already Trained Classifiers Through an Automatic Explanation-Based Learning Approach.

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Proceedings of the Discovery Science - 27th International Conference, 2024

2023

Adaptive filters in Graph Convolutional Neural Networks.

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Pattern Recognit., December, 2023

On the effects of data normalization for domain adaptation on EEG data.

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Eng. Appl. Artif. Intell., 2023

Hidden Classification Layers: a study on Data Hidden Representations with a Higher Degree of Linear Separability between the Classes.

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CoRR, 2023

Employment of Domain Adaptation Techniques in SSVEP-Based Brain-Computer Interfaces.

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IEEE Access, 2023

Impact of Nutritional Factors in Blood Glucose Prediction in Type 1 Diabetes Through Machine Learning.

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IEEE Access, 2023

Strategies to Exploit XAI to Improve Classification Systems.

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Proceedings of the Explainable Artificial Intelligence, 2023

Toward the Improvement of Probabilistic Classifiers Using Ontologies.

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Proceedings of the IEEE International Conference on Metrology for eXtended Reality, 2023

Dynamic Local Filters in Graph Convolutional Neural Networks.

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Proceedings of the Image Analysis and Processing - ICIAP 2023, 2023

An XAI-Based Masking Approach to Improve Classification Systems.

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Proceedings of the 2nd Workshop on Bias, 2023

SHAP-based Explanations to Improve Classification Systems.

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Proceedings of the 4th Italian Workshop on Explainable Artificial Intelligence co-located with 22nd International Conference of the Italian Association for Artificial Intelligence(AIxIA 2023), 2023

2022

Exploiting auto-encoders and segmentation methods for middle-level explanations of image classification systems.

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Knowl. Based Syst., 2022

Machine Learning Strategies to Improve Generalization in EEG-based Emotion Assessment: \\a Systematic Review.

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CoRR, 2022

On The Effects Of Data Normalisation For Domain Adaptation On EEG Data.

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CoRR, 2022

A Survey on EEG-Based Solutions for Emotion Recognition With a Low Number of Channels.

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IEEE Access, 2022

Reproducible Assessment of Valence and Arousal Based on an EEG Wearable Device.

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Proceedings of the IEEE International Conference on Metrology for Extended Reality, 2022

EEG-based system for Executive Function fatigue detection.

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Proceedings of the IEEE International Conference on Metrology for Extended Reality, 2022

Adoption of Machine Learning Techniques to Enhance Classification Performance in Reactive Brain-Computer Interfaces.

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Proceedings of the IEEE International Symposium on Medical Measurements and Applications, 2022

Metrological foundations of emotional valence measurement through an EEG-based system.

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Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2022

A ML-based Approach to Enhance Metrological Performance of Wearable Brain-Computer Interfaces.

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Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2022

Toward the Application of XAI Methods in EEG-based Systems.

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Proceedings of the 3rd Italian Workshop on Explainable Artificial Intelligence co-located with 21th International Conference of the Italian Association for Artificial Intelligence(AIxIA 2022), Udine, Italy, November 28, 2022

XAI Approach for Addressing the Dataset Shift Problem: BCI as a Case Study (short paper).

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Proceedings of 1st Workshop on Bias, 2022

2021

A survey on modern trainable activation functions.

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Neural Networks, 2021

A general approach for Explanations in terms of Middle Level Features.

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CoRR, 2021

Dynamic Filters in Graph Convolutional Neural Networks.

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CoRR, 2021

2020

Middle-Level Features for the Explanation of Classification Systems by Sparse Dictionary Methods.

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Int. J. Neural Syst., 2020

Preliminary validation of a measurement system for emotion recognition.

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Proceedings of the 2020 IEEE International Symposium on Medical Measurements and Applications, 2020

A General Approach to Compute the Relevance of Middle-Level Input Features.

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Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

2019

A simple and efficient architecture for trainable activation functions.

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