# Authors Title Details Date Pdf/Links/Bibtex Keywords
4 Lal U, Chikkankod V. A, Longo L.A Comparative Study on Feature Extraction Techniques for the Discrimination of Frontotemporal Dementia and Alzheimer’s Disease with Electroencephalography in Resting-State Adults Brain Sciences 2024 electroencephalography • neural signal processing • feature extraction techniques • supervised learning • deep learning • machine learning
10.3390/brainsci14040335
3Lal U., Vinayak Chikkankod A., Longo L. Fractal dimensions and machine learning for detection of Parkinson’s disease in resting-state electroencephalography Neural Computing and Applications 2024 Electroencephalography • Explainable AI • Fractal dimension • Entropy • Sliding windowing • Feature extraction • Supervised learning • Machine Learning • Deep-learning
10.1007/s00521-024-09521-4
2Chikkankod A.V., Longo L. On the Dimensionality and Utility of Convolutional Autoencoder’s Latent Space Trained with Topology-Preserving Spectral EEG Head-Maps Machine Learning and Knowledge Extraction 2022 electroencephalography • latent space analysis • sliding windowing • convolutional autoencoders • automatic feature extraction • dense neural network
10.3390/make4040053
1Gómez-Tapia C., Bozic B., Longo L.On the Minimal Amount of EEG Data Required for Learning Distinctive Human Features for Task-Dependent Biometric Applications Frontiers Neuroinformatics 2022 biometrics • EEG • feature extraction • machine learning • deep learning • graph neural networks • Electroencephalography
10.0.13.61/fninf.2022.844667
# Authors Title Details Date Pdf/Links/Bibtex Keywords