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Arash's Projects

openpnm icon openpnm

A Python package for performing pore network modeling of porous media

pconv-keras icon pconv-keras

Keras implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions"

pixelcnn icon pixelcnn

Theano reimplementation of pixelCNN architecture

pointnet icon pointnet

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

polyglot icon polyglot

Multilingual text (NLP) processing toolkit

porespy icon porespy

A set of tools for characterizing and analying 3D images of porous materials

porousmediagan icon porousmediagan

Reconstruction of three-dimensional porous media using generative adversarial neural networks

pydata-book icon pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

pytorch-openai-transformer-lm icon pytorch-openai-transformer-lm

🐥A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI

pytough icon pytough

A Python library for automating TOUGH2 simulations of subsurface fluid and heat flow

ransac-toolbox icon ransac-toolbox

A toolbox to experiment with the RANSAC algorithm for Matlab and Octave

recurrentshop icon recurrentshop

Framework for building complex recurrent neural networks with Keras

repo-2017 icon repo-2017

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning

sensor-fusion icon sensor-fusion

Use accelerometer and gyroscope data from smartphones to identify vehicle type (bus or car) and phone location (driver side or passenger side).

sensorfusion icon sensorfusion

This project performs sensor fusion to track a mobile device's orientation. The data utilised are from three sensors: a) Accelerometer, b) Magnetic Field, d) Gyroscope. The sensor fusion is executed off-line. This project basically ports code developed by Paul Lawitzki from Android to Matlab/Octave. The Matlab/Octave code imports a CSV file with a given structure. Then, a strapdown integration system is developed by computing the orientation from two different components: a) Accelerometer - Magnetic Field and b) Gravity tracking through Gyroscope. Finally, the orientations from the two components are fused.

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