Sfoglia per Autore  IERACITANO, Cosimo

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Titolo Data di pubblicazione Autore(i) File
Deep convolutional neural networks for classification of mild cognitive impaired and Alzheimer's disease patients from scalp EEG recordings 1-gen-2016 Morabito, F; Campolo, M; Ieracitano, C; Ebadi, J; Bonanno, L; De Salvo, S; Mammone, N; Bramanti, A; Bramanti, P
Investigating the brain connectivity evolution in AD and MCI patients through the EEG signals’ wavelet coherence 1-gen-2017 Ieracitano, C.; Mammone, N.; La Foresta, F.; Morabito, F. C.
A neural network approach for predicting the diameters of electrospun polyvinylacetate (PVAc) nanofibers 1-gen-2017 Ieracitano, C; Pantò, F; Frontera, P; Morabito, Francesco Carlo
Compressibility of High-Density EEG Signals in Stroke Patients 1-gen-2018 Mammone, N; De Salvo, S; Ieracitano, C; Marino, S; Cartella, E; Bramanti, A; Giorgianni, R; Morabito, Francesco Carlo
Information theoretic-based interpretation of a deep neural network approach in diagnosing psychogenic non-epileptic seizures 1-gen-2018 Gasparini, S; Campolo, M; Ieracitano, C; Mammone, N; Ferlazzo, E; Sueri, C; Tripodi, Gg; Aguglia, U; Morabito, F
METHOD FOR DETECTING A CONVERSION FROM MILD COGNITIVE IMPAIRMENT TO ALZHEIMER DISEASE 1-gen-2019 Mammone, N; Morabito, Francesco Carlo; Bramanti, P ; Bramanti, A; Campolo, M; Ieracitano, C; Bonanno, L
A Survey on the Role of Wireless Sensor Networks and IoT in Disaster Management 1-gen-2019 Adeel, Ahsan; Gogate, Mandar; Farooq, Saadullah; Ieracitano, Cosimo; Dashtipour, Kia; Larijani, Hadi; Hussain, Amir
A Machine-learning and Compressive-sensing Inspired Approach to the Optimal Array Pattern Synthesis 1-gen-2019 Morabito, A. F.; Ieracitano, C.; Morabito, F. C.
A Time-Frequency based Machine Learning System for Brain States Classification via EEG Signal Processing 1-gen-2019 Ieracitano, C.; Mammone, N.; Bramanti, A.; Marino, S.; Hussain, A.; Morabito, F. C.
Brain network analysis and deep learning models for studying neurological disorders based on EEG signal processing 16-apr-2019 Ieracitano, Cosimo
1D Convolutional Neural Network approach to classify voluntary eye blinks in EEG signals for BCI applications 1-gen-2020 Lo Giudice, M.; Varone, G.; Ieracitano, C.; Mammone, N.; Bruna, A. R.; Tomaselli, V.; Morabito, F. C.
A Convolutional Neural Network based self-learning approach for classifying neurodegenerative states from EEG signals in dementia 1-gen-2020 Ieracitano, C.; Mammone, N.; Hussain, A.; Morabito, F. C.
A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia 1-gen-2020 Ieracitano, Cosimo; Mammone, Nadia; Hussain, Amir; Morabito, Francesco C
A deep CNN approach to decode motor preparation of upper limbs from time–frequency maps of EEG signals at source level 1-gen-2020 Mammone, N.; Ieracitano, C.; Morabito, F. C.
A Convolutional Neural Network based self-learning approach for classifying neurodegenerative states from EEG signals in dementia 1-gen-2020 Ieracitano, C.; Mammone, N.; Hussain, A.; Morabito, F. C.
A novel approach to shadow boundary detection based on an adaptive direction-tracking filter for brain-machine interface applications 1-gen-2020 Ju, Z.; Gun, L.; Hussain, A.; Mahmud, M.; Ieracitano, C.
1D Convolutional Neural Network approach to classify voluntary eye blinks in EEG signals for BCI applications 1-gen-2020 Lo Giudice, M.; Varone, G.; Ieracitano, C.; Mammone, N.; Bruna, A. R.; Tomaselli, V.; Morabito, F. C.
Toward an Automatic Classification of SEM Images of Nanomaterials via a Deep Learning Approach 1-gen-2020 Ieracitano, C.; Panto, F.; Mammone, N.; Paviglianiti, A.; Frontera, P.; Morabito, F. C.
Estimating the Asymmetry of Brain Network Organization in Stroke Patients from High-Density EEG Signals 1-gen-2020 Mammone, N.; De Salvo, S.; Marino, S.; Bonanno, L.; Ieracitano, C.; Dattola, S.; La Foresta, F.; Morabito, F. C.
A novel statistical analysis and autoencoder driven intelligent intrusion detection approach 1-gen-2020 Ieracitano, C.; Adeel, A.; Morabito, F. C.; Hussain, A.
Mostrati risultati da 1 a 20 di 50
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