This repository contains code as part of my internship at GSI Technology in 2019. This contains:
- Custom ResNet neural network architecture in Keras for Signal Classification
- Code training a resnet from scratch
- Code for loading training data
- Code for extracting hamming fingerprints from signal embeddings
- Code for visualizing signal embeddings in t-SNE
- Introduction to Facebook Artificial Intelligence Similarity Search (FAISS)
- To start training from scratch, go to the notebook here:
- Here is a link to a blog I wrote describing the code: https://medium.com/gsi-technology/residual-neural-networks-in-python-1796a57c2d7
- Once you have trained your ResNet go to faiss_hamming.ipynb to extract binary fingerprints and run similarity search on the signals.
This work was inspired by:
- Over the Air Deep Learning Based Signal Classification by Tim O'Shea et. al.
- FAISS Project: https://github.com/facebookresearch/faiss/wiki/Getting-started