A General Approach to Compute the Relevance of Middle-Level Input Features. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Roberto Prevete (ICPR Workshops (3), 2020)

A ML-based Approach to Enhance Metrological Performance of Wearable Brain-Computer Interfaces. - Leopoldo Angrisani; Andrea Apicella 001; Pasquale Arpaia; Egidio De Benedetto; Nicola Donato; Luigi Duraccio; Salvatore Giugliano; Roberto Prevete (I2MTC, 2022)

Adoption of Machine Learning Techniques to Enhance Classification Performance in Reactive Brain-Computer Interfaces. - Andrea Apicella 001; Pasquale Arpaia; Andrea Cataldo; Egidio De Benedetto; Nicola Donato; Luigi Duraccio; Salvatore Giugliano; Roberto Prevete (MeMeA, 2022)

Exploiting auto-encoders and segmentation methods for middle-level explanations of image classification systems. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Roberto Prevete (Knowl. Based Syst., 2022)

SHAP-based Explanations to Improve Classification Systems. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Roberto Prevete (XAI.it@AI*IA, 2023)

An XAI-Based Masking Approach to Improve Classification Systems. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (BEWARE@AI*IA, 2023)

Assessing the Features on Blood Glucose Level Prediction in Type 1 Diabetes Patients Through Explainable Artificial Intelligence. - Giovanni Annuzzi; Pasquale Arpaia; Lutgarda Bozzetto; Sabatina Criscuolo; Salvatore Giugliano; Marisa Pesola (MetroXRAINE, 2023)

Employment of Domain Adaptation Techniques in SSVEP-Based Brain-Computer Interfaces. - Andrea Apicella 001; Pasquale Arpaia; Egidio De Benedetto; Nicola Donato; Luigi Duraccio; Salvatore Giugliano; Roberto Prevete (IEEE Access, 2023)

Improving the Performance of Already Trained Classifiers Through an Automatic Explanation-Based Learning Approach. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Roberto Prevete (DS (2), 2024)

Exploring the Latent Space of Person-Specific Convolutional Autoencoders for Eye-Blink Artefact Mitigation in EEG Signals. - Sabatina Criscuolo; Salvatore Giugliano; Andrea Apicella 001; Francesco Donnarumma; Francesco Amato 001; Annarita Tedesco; Luca Longo (RTSI, 2024)

Towards a general framework for improving the performance of classifiers using XAI methods. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Roberto Prevete (CoRR, 2024)

Enhancing EEG-Based MI-BCIs with Class-Specific and Subject-Specific Features Detected by Neural Manifold Analysis. - Mirco Frosolone; Roberto Prevete; Lorenzo Ognibeni; Salvatore Giugliano; Andrea Apicella 001; Giovanni Pezzulo; Francesco Donnarumma (Sensors, 2024)

IMPACTX: Improving Model Performance by Appropriately predicting CorrecT eXplanations. - Andrea Apicella 001; Salvatore Giugliano; Francesco Isgrò; Roberto Prevete (CoRR, 2025)