Omar Teixeira González (Omitg24)

Omitg24

Geek Repo

Company:University of Oviedo @uniovi

Location:La Felguera, Asturias, Spain

Twitter:@_omartg_24

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Omar Teixeira González's starred repositories

tensorflow

An Open Source Machine Learning Framework for Everyone

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keras

Deep Learning for humans

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AutomaticSleepStageClassifier

Sleep stage automatic classifier using CNNs and LSTMs to process frequency signals of brain activity recorded via ElectroEncephaloGram EEG. Undergraduate thesis

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luigi

Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.

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Automatic-Sleep-Stage-Classification-using-EEG-Data

Here we use EEG data to automatically classify sleep stages using neural networks built using Keras.

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Sleep-Quality-Analysis

Sleep stage classification is one of the critical methodologies for the diagnosis of sleep-related diseases and complications. The conventional method of categorization is quite clumsy and timeconsuming. This project aims to devise a deep learning and machine learning model for automatic classification of sleep stage, hence, removing the barrier of conventional method and expert ubiquity. In this work, we have considered a database that carries 197-night sleep polysomnographic data. Moreover, we aimed to classify this data into stages W, N1, N2, N3 and N4 as mentioned in the AASM standard. In addition to that, we have selected the EEG FpzCz channel because of its better quality and used an epoch time of 30 seconds for signal processing. We have used four machine learning and deep learning methods, namely CNN-CNN, CNN-LSTM, Random Forest, and XGBoosting, with 82%, 87%, 51%, and 59%, respectively. This report has depicted a roadmap of the EEG-based sleep stage scoring method by implementing the state of art methods. In conclusion, using better signal processing techniques will increase the overall performance and accuracy of the model.

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sleep-classification

Sleep stage classification using LSTM networks

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SleepEEGNet

SleepEEGNet: Automated Sleep Stage Scoring with Sequence to Sequence Deep Learning Approach

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tinysleepnet

TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College London respectively

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deepsleepnet

DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

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Sleep-stage-classification

Sleep stage classification based on Recurrent neural networks using wrist-worn device data

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awesome-pipeline

A curated list of awesome pipeline toolkits inspired by Awesome Sysadmin

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thefuck

Magnificent app which corrects your previous console command.

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DetectDee

DetectDee: Hunt down social media accounts by username, email or phone across social networks.

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Prost-Drink

Repositorio con todo el código y documentación sobre el juego de beber

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python-machine-learning-book-2nd-edition

The "Python Machine Learning (2nd edition)" book code repository and info resource

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tsplib95

Library for working with TSPLIB files.

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lomap_es3a

LoMap Software architecture group es3a course 2022_23 - GOMap!® application, which provides maps where the user can add markers and obtain more information about a specific location. Read our documentation at: https://arquisoft.github.io/lomap_es3a/

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emoji-cheat-sheet

A markdown version emoji cheat sheet

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