MikeMpapa

CNNs-Audio-Emotion-Recognition

CNNs-Speech-Music-Discrimination

A deep learning framework for Speech-Music discrimination of continuous audio streams

CogBeacon-MultiModal_Dataset_for_Cognitive_Fatigue

CogBeacon is a multi-modal dataset designed to target the effects of cognitive fatigue in human performance. The dataset consists of 76 sessions collected from 19 male and female users performing different versions of the Wisconsin Card Sorting Test (WCST); a popular cognitive test in experimental and clinical psychology designed to assess cognitive flexibility, reasoning and specific aspects of cognitive functioning. During each session we record and fully annotate, user's EEG functionality, facial keypoints, real-time self-reports on cognitive fatigue, as well as detailed information of the performance metrics achieved during the cognitive task (success rate, response time, number of errors etc.). Along with the dataset we provide a baseline Machine Learning analysis towards predicting cognitive fatigue and our multi-modal implementation of the WCST, to allow other researches expand or modify the functionalities of the CogBeacon data-collection framework. To our knowledge, this is the first multi-modal dataset specifically designed to assess cognitive fatigue.

CogBeacon-WCST_interface

EEG-Dataset--Sequence-Learning

EEG Dataset for the paper: Towards Predicting Task Performance from EEG Signals

MLEmg_Monitoring_Physical_Fatigue

EMG Machine Learning Analysis and Feature Extraction for Physical Fatigue Monitoring

Motion-Tracker

A motion tracking tool of multiple objects (up to 7) implemented in matlab

MUSE-EEG-DeepLearning

Sequence-Learning-Cognive-Task-EEG-Performance-Prediction

A machine learning approach to process EEG signals from the sequence task provided by https://github.com/TsiakasK/sequence-learning.git

sklearn_wrapper

A wrapper to simplify the ussage of sklearn for massive experimentation with different modeling methods

MikeMpapa/CogBeacon-MultiModal_Dataset_for_Cognitive_Fatigue

CogBeacon is a multi-modal dataset designed to target the effects of cognitive fatigue in human performance. The dataset consists of 76 sessions collected from 19 male and female users performing different versions of the Wisconsin Card Sorting Test (WCST); a popular cognitive test in experimental and clinical psychology designed to assess cognitive flexibility, reasoning and specific aspects of cognitive functioning. During each session we record and fully annotate, user's EEG functionality, facial keypoints, real-time self-reports on cognitive fatigue, as well as detailed information of the performance metrics achieved during the cognitive task (success rate, response time, number of errors etc.). Along with the dataset we provide a baseline Machine Learning analysis towards predicting cognitive fatigue and our multi-modal implementation of the WCST, to allow other researches expand or modify the functionalities of the CogBeacon data-collection framework. To our knowledge, this is the first multi-modal dataset specifically designed to assess cognitive fatigue.

MikeMpapa/MLEmg_Monitoring_Physical_Fatigue

EMG Machine Learning Analysis and Feature Extraction for Physical Fatigue Monitoring

MikeMpapa/CogBeacon-WCST_interface

MikeMpapa/sklearn_wrapper

A wrapper to simplify the ussage of sklearn for massive experimentation with different modeling methods

MikeMpapa/lit-llama

Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.

MikeMpapa/lmd_gpt2

Hugging Face implementation to train a GPT-2 model on LMD logging in WandB

MikeMpapa/midi-model

Midi event transformer for music generation

MikeMpapa/VideoHandlerClass

A module to handle videos

MikeMpapa/AudioEditingCode

MikeMpapa/audioset_tagging_cnn

MikeMpapa/ChatMusician

MikeMpapa/CityNet

A neural network classifier for urban soundscapes

MikeMpapa/DeepLabCut

Markerless pose estimation of user-defined features with deep learning for all animals, including humans

MikeMpapa/ear-landmark-detection-with-CNN

A tool to detect 55 landmark points on a given ear image.

MikeMpapa/examples

TensorFlow examples

MikeMpapa/face-alignment

:fire: 2D and 3D Face alignment library build using pytorch

MikeMpapa/fadtk

A simple library for Fréchet Audio Distance (FAD) calculation

MikeMpapa/fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

MikeMpapa/labelpix

labelpix is a graphical image labeling interface for drawing bounding boxes

MikeMpapa/LLaMA-Factory

Unify Efficient Fine-Tuning of 100+ LLMs

MikeMpapa/mmm_tokenizer_multitrack_midi

MikeMpapa/musiclang_predict

AI Prediction api of the MusicLang package

MikeMpapa/photoguard

Raising the Cost of Malicious AI-Powered Image Editing

MikeMpapa/pytorch-transformers

👾 A library of state-of-the-art pretrained models for Natural Language Processing (NLP)

MikeMpapa/shap

A game theoretic approach to explain the output of any machine learning model.

MikeMpapa/StartupDataScience

MikeMpapa/SwiftUI

A SwiftUI playground based on https://www.hackingwithswift.com/100/swiftui

MikeMpapa/TchAIkovsky

Using JAX to generate piano music as MIDI

MikeMpapa/yolov3-keras-tf2

yolo implementation in keras and tensorflow 2.2

MikeMpapa/yolov4-tiny-custom_Training