Nadia Mammone
Orcid: 0000-0003-4962-3500
According to our database1,
Nadia Mammone
authored at least 83 papers
between 2004 and 2024.
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Bibliography
2024
A Few-Shot Transfer Learning Approach for Motion Intention Decoding from Electroencephalographic Signals.
Int. J. Neural Syst., February, 2024
2023
IEEE J. Biomed. Health Informatics, May, 2023
2022
A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls.
Sensors, 2022
A novel explainable machine learning approach for EEG-based brain-computer interface systems.
Neural Comput. Appl., 2022
A fuzzy-enhanced deep learning approach for early detection of Covid-19 pneumonia from portable chest X-ray images.
Neurocomputing, 2022
A Conditional Generative Adversarial Network and Transfer Learning-Oriented Anomaly Classification System for Electrospun Nanofibers.
Int. J. Neural Syst., 2022
Permutation Entropy-Based Interpretability of Convolutional Neural Network Models for Interictal EEG Discrimination of Subjects with Epileptic Seizures vs. Psychogenic Non-Epileptic Seizures.
Entropy, 2022
A Deep Cognitive Venetian Blinds System for Automatic Estimation of Slat Orientation.
Cogn. Comput., 2022
Efficient Deep Neural Networks for Classification of Alzheimer's Disease and Mild Cognitive Impairment from Scalp EEG Recordings.
Cogn. Comput., 2022
Visual Explanations of Deep Convolutional Neural Network for eye blinks detection in EEG-based BCI applications.
Proceedings of the International Joint Conference on Neural Networks, 2022
Detection of Covid-19 Pneumonia from chest X-ray images: joint use of ECovNNet and fuzzy distance.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2022
Proceedings of the IEEE International Conference on Omni-layer Intelligent Systems, 2022
Decoding Motor Preparation Through a Deep Learning Approach Based on EEG Time-Frequency Maps.
AII, 2022
Explainable Deep Learning Classification of Respiratory Sound for Telemedicine Applications.
AII, 2022
2021
A Hybrid-Domain Deep Learning-Based BCI For Discriminating Hand Motion Planning From EEG Sources.
Int. J. Neural Syst., 2021
Micropumps for drug delivery systems: a new semi-linear elliptic boundary-value problem.
Comput. Appl. Math., 2021
MPnnet: a Motion Planning Decoding Convolutional Neural Network for EEG-based Brain Computer Interfaces.
Proceedings of the International Joint Conference on Neural Networks, 2021
Toward an Augmented and Explainable Machine Learning Approach for Classification of Defective Nanomaterial Patches.
Proceedings of the 22nd Engineering Applications of Neural Networks Conference, 2021
2020
Estimating the Asymmetry of Brain Network Organization in Stroke Patients from High-Density EEG Signals.
Proceedings of the Neural Approaches to Dynamics of Signal Exchanges, 2020
Toward an Automatic Classification of SEM Images of Nanomaterials via a Deep Learning Approach.
Proceedings of the Neural Approaches to Dynamics of Signal Exchanges, 2020
Proceedings of the Neural Approaches to Dynamics of Signal Exchanges, 2020
A deep CNN approach to decode motor preparation of upper limbs from time-frequency maps of EEG signals at source level.
Neural Networks, 2020
A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia.
Neural Networks, 2020
A Convolutional Neural Network based self-learning approach for classifying neurodegenerative states from EEG signals in dementia.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
1D Convolutional Neural Network approach to classify voluntary eye blinks in EEG signals for BCI applications.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
2019
Proceedings of the Quantifying and Processing Biomedical and Behavioral Signals, 2019
Evolution Characterization of Alzheimer's Disease Using eLORETA's Three-Dimensional Distribution of the Current Density and Small-World Network.
Proceedings of the Quantifying and Processing Biomedical and Behavioral Signals, 2019
Brain Network Analysis of Compressive Sensed High-Density EEG Signals in AD and MCI Subjects.
IEEE Trans. Ind. Informatics, 2019
Leveraging network analysis to support experts in their analyses of subjects with MCI and AD.
Medical Biol. Eng. Comput., 2019
A Convolutional Neural Network approach for classification of dementia stages based on 2D-spectral representation of EEG recordings.
Neurocomputing, 2019
A network analysis based approach to characterizing periodic sharp wave complexes in electroencephalograms of patients with sporadic CJD.
Int. J. Medical Informatics, 2019
Int. J. Data Min. Model. Manag., 2019
A Time-Frequency based Machine Learning System for Brain States Classification via EEG Signal Processing.
Proceedings of the International Joint Conference on Neural Networks, 2019
2018
Proceedings of the Multidisciplinary Approaches to Neural Computing, 2018
Investigating the Brain Connectivity Evolution in AD and MCI Patients Through the EEG Signals' Wavelet Coherence.
Proceedings of the Multidisciplinary Approaches to Neural Computing, 2018
Permutation Jaccard Distance-Based Hierarchical Clustering to Estimate EEG Network Density Modifications in MCI Subjects.
IEEE Trans. Neural Networks Learn. Syst., 2018
Information Theoretic-Based Interpretation of a Deep Neural Network Approach in Diagnosing Psychogenic Non-Epileptic Seizures.
Entropy, 2018
2017
Deep Learning Representation from Electroencephalography of Early-Stage Creutzfeldt-Jakob Disease and Features for Differentiation from Rapidly Progressive Dementia.
Int. J. Neural Syst., 2017
Permutation Disalignment Index as an Indirect, EEG-Based, Measure of Brain Connectivity in MCI and AD Patients.
Int. J. Neural Syst., 2017
A Permutation Disalignment Index-Based Complex Network Approach to Evaluate Longitudinal Changes in Brain-Electrical Connectivity.
Entropy, 2017
Usage of network analysis to investigate Periodic Sharp Wave Complexes in EEGs of patients with sporadic CJD.
Proceedings of the 25th Italian Symposium on Advanced Database Systems, 2017
A complex network-based approach to detecting and characterizing ictal states in patients with Childhood Absence Epilepsy.
Proceedings of the 3rd IEEE International Forum on Research and Technologies for Society and Industry, 2017
Wavelet coherence-based clustering of EEG signals to estimate the brain connectivity in absence epileptic patients.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017
SoCNNet: An Optimized Sobel Filter Based Convolutional Neural Network for SEM Images Classification of Nanomaterials.
Proceedings of the Advances in Intelligent Information Hiding and Multimedia Signal Processing, 2017
Proceedings of the Advances in Intelligent Information Hiding and Multimedia Signal Processing, 2017
2016
Proceedings of the Advances in Neural Networks - Computational Intelligence for ICT, 2016
Deep convolutional neural networks for classification of mild cognitive impaired and Alzheimer's disease patients from scalp EEG recordings.
Proceedings of the 2nd IEEE International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow, 2016
Longitudinal study of alzheimer's disease degeneration through EEG data analysis with a NeuCube spiking neural network model.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016
Hierarchical clustering of the electroencephalogram spectral coherence to study the changes in brain connectivity in Alzheimer's disease.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016
2015
Proceedings of the Advances in Neural Networks: Computational and Theoretical Issues, 2015
A Feasibility Study of Using the NeuCube Spiking Neural Network Architecture for Modelling Alzheimer's Disease EEG Data.
Proceedings of the Advances in Neural Networks: Computational and Theoretical Issues, 2015
Differentiating Interictal and Ictal States in Childhood Absence Epilepsy through Permutation Rényi Entropy.
Entropy, 2015
Learning Vector Quantization and Permutation Entropy to analyse epileptic electroencephalography.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
Modelling Absence Epilepsy seizure data in the NeuCube evolving spiking neural network architecture.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
2014
Enhanced Automatic Wavelet Independent Component Analysis for Electroencephalographic Artifact Removal.
Entropy, 2014
2013
Erratum: "Analysis of Absence seizure Generation using EEG Spatial-Temporal Regularity Measures".
Int. J. Neural Syst., 2013
SVM classification of epileptic EEG recordings through multiscale permutation entropy.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013
2012
Analysis of Absence Seizure Generation using EEG Spatial-Temporal Regularity Measures.
Int. J. Neural Syst., 2012
2011
Neural Comput. Appl., 2011
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011
2010
Discovering Network Phenomena in the Epileptic Electroencephalography through Permutation Entropy Mapping.
Proceedings of the Neural Nets WIRN10, 2010
2009
PCA-ICA for automatic identification of critical events in continuous coma-EEG monitoring.
Biomed. Signal Process. Control., 2009
Algorithms and topographic mapping for epileptic seizures recognition and prediction.
Proceedings of the Neural Nets WIRN09, 2009
Proceedings of the Neural Nets WIRN09, 2009
Proceedings of the International Joint Conference on Neural Networks, 2009
2008
Enhanced automatic artifact detection based on independent component analysis and Renyi's entropy.
Neural Networks, 2008
Proceedings of the New Directions in Neural Networks, 2008
Proceedings of the New Directions in Neural Networks, 2008
Mutual information for measuring independence of STLmax time series in the epileptic brain.
Proceedings of the International Joint Conference on Neural Networks, 2008
2007
Multiresolution ICA for Artifact Identification from Electroencephalographic Recordings.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2007
Information Theoretic Learning for Inverse Problem Resolution in Bio-electromagnetism.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2007
Wavelet-ICA methodology for efficient artifact removal from Electroencephalographic recordings.
Proceedings of the International Joint Conference on Neural Networks, 2007
2006
Automatic Detection of Critical Epochs in coma-EEG Using Independent Component Analysis and Higher Order Statistics.
Proceedings of the Neural Information Processing, 13th International Conference, 2006
Visualization of the Short Term Maximum Lyapunov Exponent Topography in the Epileptic Brain.
Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006
Analysis of the Automatic Detection of Critical Epochs from coma-EEG by Dominant Components and Features Extraction.
Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006
2005
Proceedings of the Neural Nets, 16th Italian Workshop on Neural Nets, 2005
Artificial Neural Networks for Classifying Magnetic Measurements in Tokamak Reactors.
Proceedings of the International Enformatika Conference, 2005
Semi-Automatic Artifact Rejection Procedure based on Kurtosis, Renyi's Entropy and Independent Component Scalp Maps.
Proceedings of the International Enformatika Conference, 2005
A new approach based on wavelet-ICA algorithms for fetal electrocardiogram extraction.
Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005
2004
Proceedings of the Biological and Artificial Intelligence Environments, 2004