DCT Perceptron Layer: A Transform Domain Approach for Convolution Layer. (arXiv:2211.08577v1 [cs.CV])

In this paper, we propose a novel Discrete Cosine Transform (DCT)-based
neural network layer which we call DCT-perceptron to replace the $3\times3$
Conv2D layers in the Residual neural Network (ResNet). Convolutional filtering
operations are performed in the DCT domain using element-wise multiplications
by taking advantage of the Fourier and DCT Convolution theorems. A trainable
soft-thresholding layer is used as the nonlinearity in the DCT perceptron.
Compared to ResNet's Conv2D layer which is spatial-agnostic and
channel-specific, the proposed layer is location-specific …

arxiv convolution perceptron