Exploiting Context Information for Image Description. - Andrea Apicella 001; Anna Corazza; Francesco Isgrò; Giuseppe Vettigli (ICIAP (1), 2017)

Improving Face Recognition in Low Quality Video Sequences: Single Frame vs Multi-frame Super-Resolution. - Andrea Apicella 001; Francesco Isgrò; Daniel Riccio (ICIAP (1), 2017)

Integrating a Priori Probabilistic Knowledge into Classification for Image Description. - Andrea Apicella 001; Anna Corazza; Francesco Isgrò; Giuseppe Vettigli (WETICE, 2017)

Integration of Context Information through Probabilistic Ontological Knowledge into Image Classification. - Andrea Apicella 001; Anna Corazza; Francesco Isgrò; Giuseppe Vettigli (Inf., 2018)

Improving classification models with context knowledge and variable activation functions. - Andrea Apicella 001 (2018)

Sparse Dictionaries for the Explanation of Classification Systems. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete; Guglielmo Tamburrini; Alessio Vietri (PIE@CAiSE, 2019)

Explaining classification systems using sparse dictionaries. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete; Andrea Sorrentino; Guglielmo Tamburrini (ESANN, 2019)

Contrastive Explanations to Classification Systems Using Sparse Dictionaries. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete; Guglielmo Tamburrini (ICIAP (1), 2019)

A simple and efficient architecture for trainable activation functions. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete (Neurocomputing, 2019)

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)

Preliminary validation of a measurement system for emotion recognition. - Andrea Apicella 001; Pasquale Arpaia; Giovanna Mastrati; Nicola Moccaldi; Roberto Prevete (MeMeA, 2020)

Middle-Level Features for the Explanation of Classification Systems by Sparse Dictionary Methods. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete; Guglielmo Tamburrini (Int. J. Neural Syst., 2020)

Dynamic Filters in Graph Convolutional Neural Networks. - Andrea Apicella 001; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (CoRR, 2021)

A general approach for Explanations in terms of Middle Level Features. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete (CoRR, 2021)

A survey on modern trainable activation functions. - Andrea Apicella 001; Francesco Donnarumma; Francesco Isgrò; Roberto Prevete (Neural Networks, 2021)

XAI Approach for Addressing the Dataset Shift Problem: BCI as a Case Study (short paper). - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete (BEWARE@AI*IA, 2022)

Toward the Application of XAI Methods in EEG-based Systems. - Andrea Apicella 001; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (XAI.it@AI*IA, 2022)

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)

Metrological foundations of emotional valence measurement through an EEG-based system. - Andrea Apicella 001; Pasquale Arpaia; Antonio Esposito 002; Giovanna Mastrati; Nicola Moccaldi (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)

EEG-based system for Executive Function fatigue detection. - Andrea Apicella 001; Pasquale Arpaia; Paolo De Blasiis; Anna Della Calce; Allegra Fullin; Ludovica Gargiulo; Luigi Maffei; Francesca Mancino; Nicola Moccaldi; Andrea Pollastro; Ersilia Vallefuoco (MetroXRAINE, 2022)

Reproducible Assessment of Valence and Arousal Based on an EEG Wearable Device. - Andrea Apicella 001; Pasquale Arpaia; Andrea Cataldo; Giovanni D'Errico; Davide Marocco; Giovanna Mastrati; Nicola Moccaldi; Andrea Pollastro; Bernadette Ricciardi; Ersilia Vallefuoco (MetroXRAINE, 2022)

A Survey on EEG-Based Solutions for Emotion Recognition With a Low Number of Channels. - Andrea Apicella 001; Pasquale Arpaia; Francesco Isgrò; Giovanna Mastrati; Nicola Moccaldi (IEEE Access, 2022)

On The Effects Of Data Normalisation For Domain Adaptation On EEG Data. - Andrea Apicella 001; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (CoRR, 2022)

Machine Learning Strategies to Improve Generalization in EEG-based Emotion Assessment: a Systematic Review. - Andrea Apicella 001; Pasquale Arpaia; Giovanni D'Errico; Davide Marocco; Giovanna Mastrati; Nicola Moccaldi; Roberto Prevete (CoRR, 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)

Dynamic Local Filters in Graph Convolutional Neural Networks. - Andrea Apicella 001; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (ICIAP (2), 2023)

Toward the Improvement of Probabilistic Classifiers Using Ontologies. - Andrea Apicella 001; Anna Corazza; Francesco Isgrò; Roberto Prevete (MetroXRAINE, 2023)

Strategies to Exploit XAI to Improve Classification Systems. - Andrea Apicella 001; Luca Di Lorenzo; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (xAI (1), 2023)

Impact of Nutritional Factors in Blood Glucose Prediction in Type 1 Diabetes Through Machine Learning. - Giovanni Annuzzi; Andrea Apicella 001; Pasquale Arpaia; Lutgarda Bozzetto; Sabatina Criscuolo; Egidio De Benedetto; Marisa Pesola; Roberto Prevete; Ersilia Vallefuoco (IEEE Access, 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)

Hidden Classification Layers: a study on Data Hidden Representations with a Higher Degree of Linear Separability between the Classes. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete (CoRR, 2023)

On the effects of data normalization for domain adaptation on EEG data. - Andrea Apicella 001; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (Eng. Appl. Artif. Intell., 2023)

Adaptive filters in Graph Convolutional Neural Networks. - Andrea Apicella 001; Francesco Isgrò; Andrea Pollastro; Roberto Prevete (Pattern Recognit., 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)

Advancing Healthcare Through AI: Innovations in Monitoring and Diagnostic Technologies at the Augmented Reality for Health Monitoring Laboratory (ARHeMLab). - Giovanni Annuzzi; Andrea Apicella 001; Pasquale Arpaia; Lutgarda Bozzetto; Umberto Bracale; Egidio De Benedetto; Paolo De Blasiis; Antonio Esposito 002; Francesco Isgrò; Giacomo Lus; Nicola Moccaldi; Roberto Peltrini; et al. (Ital-IA, 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)

Toward cross-subject and cross-session generalization in EEG-based emotion recognition: Systematic review, taxonomy, and methods. - Andrea Apicella 001; Pasquale Arpaia; Giovanni D'Errico; Davide Marocco; Giovanna Mastrati; Nicola Moccaldi; Roberto Prevete (Neurocomputing, 2024)

Hidden classification layers: Enhancing linear separability between classes in neural networks layers. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete (Pattern Recognit. Lett., 2024)

Exploring Nutritional Influence on Blood Glucose Forecasting for Type 1 Diabetes Using Explainable AI. - Giovanni Annuzzi; Andrea Apicella 001; Pasquale Arpaia; Lutgarda Bozzetto; Sabatina Criscuolo; Egidio De Benedetto; Marisa Pesola; Roberto Prevete (IEEE J. Biomed. Health Informatics, 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)

Interpreting the latent space of a Convolutional Variational Autoencoder for semi-automated eye blink artefact detection in EEG signals. - Sabatina Criscuolo; Andrea Apicella 001; Roberto Prevete; Luca Longo (Comput. Stand. Interfaces, 2025)

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

Domain Adaptation for Fear of Heights Classification in a VR Environment Based on EEG and ECG. - Andrea Apicella 001; Pasquale Arpaia; Simone Barbato; Giovanni D'Errico; Giovanna Mastrati; Nicola Moccaldi; Ersilia Vallefuoco; Selina Christin Wriessnegger (Inf. Syst. Frontiers, 2025)

Don't push the button! Exploring data leakage risks in machine learning and transfer learning. - Andrea Apicella 001; Francesco Isgrò; Roberto Prevete (Artif. Intell. Rev., 2025)