Efficient Harmonic Neural Networks with Compound Discrete Cosine Transform filters and Shared Reconstruction filters
This code was developed and tested with Python3.6, Pytorch 1.5 and CUDA 10.2 on Ubuntu 18.04.5.
You are able to run the provided demo code.
''' mkdir logs
sh train_cifar.sh '''
If you found our research helpful or influential please consider citing
@ARTICLE{9783450, author={Lu, Yao and Zhang, Le and Yang, Xiaofei and Zhou, Yicong}, journal={IEEE Transactions on Neural Networks and Learning Systems}, title={Efficient Harmonic Neural Networks With Compound Discrete Cosine Transform Filters and Shared Reconstruction Filters}, year={2022}, volume={}, number={}, pages={1-15}, doi={10.1109/TNNLS.2022.3176611}}