timqqt / mera_image_classification

MERA tensor network for tiny object image classification

MERA_Image_Classification

Code Contributor: Fanjie Kong

Finished Work:

1. Implemented 2D MERA model using PyTorch and TensorFlow. TensorFlow version is more time-efficient.
2. Tested our 2D MERA model on MNIST, NeedleMNIST(64x64, 128x128) and LIDC dataset.

	MNIST	NeedleMNIST(64x64)	NeedleMNIST(128x128)	LIDC
CNN	0.983	0.760	0.739	0.780
Tensor-NN	0.985	0.740	0.727	0.860
2D MERA	0.903	0.784	0.714	0.760

3. Summarized our work into a paper submitted to QTNML 2020

Description:

PyTorch codes:

• Basic Pytorch dependency
• Tested on Pytorch 1.3, Python 3.6
• Unzip the data and point the path to --data_path
• How to run tests: python train.py --data_path data_location

TensorFlow code:

• TensorFlow 2.1.0 and TensorNetwork
• Experiments are performed on Jupyter Notebook MERA_MNIST.ipynb

Thanks to the following repositories:

• https://github.com/raghavian/loTeNet_pytorch