Radio Frequency Machine Learning with PyTorch

Motor Imagery EEG Signal Classification Using Random Subspace Ensemble Network

Detection of human emotions from eeg signals using the amigos dataset

Code for "Complex-Valued Depthwise Separable Convolutional Neural Network for Automatic Modulation Classification"

This repository contains the implementation of the modified convolutional neural network (MCNN) for classification of Frequency-Hopping Spread Spectrum Signals using the time-frequency representations (TFRs) as an images.

Classification of biosignals, including EEG and MEG, through feature extraction in the time and frequency domains using machine learning methods.

AtrialFibrillation-Classification-SMoLK is a deep learning project designed to classify arrhythmias, specifically focusing on atrial fibrillation (Afib), using the MIT-BIH Arrhythmia Database. The project leverages a neural network model with learned filters to achieve high classification accuracy across multiple classes.

📈 Análise e processamento de sinais com SVD

Real-time robot collision detection using supervised learning methods

Deep Leaning for Classification of drone signals.

VBS Power Line Fault Detection (Kaggle challenge)

A deep learning project classifying ECG signals using time series models

One of the firsts dataset level explanability libraries for 1d signal using GRAD-CAM++

This project uses time-domain EMG signal features to classify gender (male/female) via various machine learning models. It explores multiple resampling techniques (SMOTE, ADASYN, etc.) to handle class imbalance and compares model performance using cross-validation and test accuracy. Visual plots a