This repository contains multiple Jupyter notebooks which were used for the implementation part of the paper Measuring what Really Matters: Optimizing Neural Networks for TinyML. This repository contains the trained models which were evaluated and deployed on microcontrollers:
- LeNet5 on MNIST
- ResNet-20 on CIFAR-10
- Dense layers benchmarking
- Convolutional layers benchmarking
- Depth-wise convolutional layers benchmarking
The models were trained and saved as a Keras file by using TensorFlow.
For the conversion process to .tflite
see the toolchain repository.