ejhusom/DeepPower

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ejhusom/DeepPower

ejhusom

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Estimate effort during exercise using deep learning. Power estimation based on breathing patterns.

d2m

A machine learning pipeline taking you from raw data to fully trained machine learning model - from data to model (d2m).

Erdre

Erroneous data repair for Industry 4.0. Machine learning pipeline using DVC.

respiratory-inductive-plethysmography-for-power-prediction-data

Respiratory inductive plethysmography data and power output collected during cycling workouts. Used in thesis: http://urn.nb.no/URN:NBN:no-89899

green-ai

A curated list of Green AI resources.

FYS-STK4155

Source code for the course FYS-STK4155 Applied Data Analysis and Machine Learning at University of Oslo.

peakbase

Minimalist tool for peak baggers. Manage and visualize your collection of mountain summits privately in the browser.

healthAI

Android app for applying machine learning in the health and wellness domain.

FYS3150

Source code for the course FYS3150 Computational Physics at University of Oslo.

FYS-STK4155-project-3

Classifying human activity using tree ensembles.

ejhusom.github.io

Projects by Erik Johannes Husom.

RespiratoryPatterns

Recognizing respiratory rate and patterns from abdominal movement.

inGen

MELODI

Jupyter Notebook