Andrea Apicella

Orcid: 0000-0002-5391-168X

Affiliations:
  • Università degli Studi di Napoli Federico II, Napoli, Italy


According to our database1, Andrea Apicella authored at least 38 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2024
Hidden classification layers: Enhancing linear separability between classes in neural networks layers.
Pattern Recognit. Lett., January, 2024

Towards a general framework for improving the performance of classifiers using XAI methods.
CoRR, 2024

Don't Push the Button! Exploring Data Leakage Risks in Machine Learning and Transfer Learning.
CoRR, 2024

2023
Adaptive filters in Graph Convolutional Neural Networks.
Pattern Recognit., December, 2023

On the effects of data normalization for domain adaptation on EEG data.
Eng. Appl. Artif. Intell., 2023

Hidden Classification Layers: a study on Data Hidden Representations with a Higher Degree of Linear Separability between the Classes.
CoRR, 2023

Employment of Domain Adaptation Techniques in SSVEP-Based Brain-Computer Interfaces.
IEEE Access, 2023

Impact of Nutritional Factors in Blood Glucose Prediction in Type 1 Diabetes Through Machine Learning.
IEEE Access, 2023

Strategies to Exploit XAI to Improve Classification Systems.
Proceedings of the Explainable Artificial Intelligence, 2023

Toward the Improvement of Probabilistic Classifiers Using Ontologies.
Proceedings of the IEEE International Conference on Metrology for eXtended Reality, 2023

Dynamic Local Filters in Graph Convolutional Neural Networks.
Proceedings of the Image Analysis and Processing - ICIAP 2023, 2023

An XAI-Based Masking Approach to Improve Classification Systems.
Proceedings of the 2nd Workshop on Bias, 2023

SHAP-based Explanations to Improve Classification Systems.
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.
Knowl. Based Syst., 2022

Machine Learning Strategies to Improve Generalization in EEG-based Emotion Assessment: \\a Systematic Review.
CoRR, 2022

On The Effects Of Data Normalisation For Domain Adaptation On EEG Data.
CoRR, 2022

A Survey on EEG-Based Solutions for Emotion Recognition With a Low Number of Channels.
IEEE Access, 2022

Reproducible Assessment of Valence and Arousal Based on an EEG Wearable Device.
Proceedings of the IEEE International Conference on Metrology for Extended Reality, 2022

EEG-based system for Executive Function fatigue detection.
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.
Proceedings of the IEEE International Symposium on Medical Measurements and Applications, 2022

Metrological foundations of emotional valence measurement through an EEG-based system.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2022

A ML-based Approach to Enhance Metrological Performance of Wearable Brain-Computer Interfaces.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2022

Toward the Application of XAI Methods in EEG-based Systems.
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).
Proceedings of 1st Workshop on Bias, 2022

2021
A survey on modern trainable activation functions.
Neural Networks, 2021

A general approach for Explanations in terms of Middle Level Features.
CoRR, 2021

Dynamic Filters in Graph Convolutional Neural Networks.
CoRR, 2021

2020
Middle-Level Features for the Explanation of Classification Systems by Sparse Dictionary Methods.
Int. J. Neural Syst., 2020

Preliminary validation of a measurement system for emotion recognition.
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.
Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

2019
A simple and efficient architecture for trainable activation functions.
Neurocomputing, 2019

Contrastive Explanations to Classification Systems Using Sparse Dictionaries.
Proceedings of the Image Analysis and Processing - ICIAP 2019, 2019

Explaining classification systems using sparse dictionaries.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Sparse Dictionaries for the Explanation of Classification Systems.
Proceedings of the 1st International Workshop on Processing Information Ethically co-located with 31st International Conference on Advanced Information Systems Engineering, 2019

2018
Integration of Context Information through Probabilistic Ontological Knowledge into Image Classification.
Inf., 2018

2017
Integrating a Priori Probabilistic Knowledge into Classification for Image Description.
Proceedings of the 26th IEEE International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises, 2017

Improving Face Recognition in Low Quality Video Sequences: Single Frame vs Multi-frame Super-Resolution.
Proceedings of the Image Analysis and Processing - ICIAP 2017, 2017

Exploiting Context Information for Image Description.
Proceedings of the Image Analysis and Processing - ICIAP 2017, 2017


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