Abstract: Federated learning is increasingly being considered for sensor-driven human activity recognition, offering advantages in terms of privacy and scalability compared to centralized methods.
A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
ImmunoStruct is a multimodal deep learning framework that integrates sequence, structural, and biochemical information to predict multi-allele class-I peptide-MHC immunogenicity. By leveraging ...
The project explores multiple machine learning approaches including traditional ML models (Logistic Regression, SVM, Naive Bayes) and ensemble methods (Random Forest, XGBoost, Voting Classifier).
Abstract: In recent years, brain-computer interfaces (BCIs) leveraging electroencephalography (EEG) signals for the control of external devices have garnered increasing attention. The information ...