IEEE

EEG Motor Execution Classification Using RG-CNN-LSTM: A Riemannian Geometry-Inspired Deep Learning Approach

Abstract: Detecting motor-related brain activity is essential for advancements in brain-computer interface (BCI) applications, particularly in neurorehabilitation and assistive technologies. While ...
IEEE

EEG-Based Four Level Fear Classification using Graph Neural Network and LSTM Fusion Model: Comparing Raw and DE Features with k-Fold and Leave-One-Subject-Out

Abstract: Electroencephalography (EEG)-based four-level fear classification is important for mental-health assessment and emotion-aware systems, yet robust generalization to unseen subjects remains ...
GitHub

dictionary-based-classification

End-to-End Python implementation of Muço’s (2025) corruption measurement framework. Combines NLP pipeline (regex extraction, Porter stemming, TF-IDF), PCA-based dimensionality reduction, and ...