/Place-Recognition-using-Autoencoders-and-NN

Place recognition with WiFi fingerprints using Autoencoders and Neural Networks

Primary LanguageJupyter NotebookApache License 2.0Apache-2.0

Place recognition with WiFi fingerprints using Autoencoders and Neural Networks

Tensorflow implementation of model discussed in the following paper: Low-effort place recognition with WiFi fingerprints using deep learning

Tools Required

Python 3 is used during development and following libraries are required to run the code provided in the notebook:

  • Tensorflow
  • Numpy
  • Pandas

Dataset

The UJIIndoorLoc dataset used for model training and testing, can be downloaded from the following [link].

Note: If you see mistakes or want to suggest changes, please submit a pull request.