In this paper, we tackle the high computational overhead of transformers for lightweight image super-resolution. (SR). Motivated by the observations of self-attention's inter-layer repetition, we ...

Abstract: Graph Convolution Networks (GCNs) have achieved remarkable success in representation of structured graph data. As we know that traditional GCNs are generally defined on the fixed first-order ...

Abstract: Convolution is fundamental in digital signal processing across many applications. Existing works enable N-point linear convolution via N-point right-angle circular convolution (RCC) based on ...

This repo is the official implementation of Efficient 3D Recognition with Event-driven Spike Sparse Convolution. It currently concludes codes and models for the following tasks: 3D Classification: See ...

A windowed sinc filter outperforms a moving-average filter in the frequency domain. Figure 1. The ideal filter X(f) in the frequency domain has a gain of 1 and a cutoff frequency fC. This result is in ...

Convolution is used in a variety of signal-processing applications, including time-domain-waveform filtering. In a recent series on the inverse fast Fourier transform (FFT), we concluded with a ...

Introduction: The accurate determination of the ocean sound speed profile (SSP) is essential for oceanographic research and marine engineering. Traditional methods for acquiring SSP data are often ...

ABSTRACT: One of the most dangerous forms of cancer, skin cancer has been on the rise over the past ten years. Nonetheless, melanoma detection is a method that uses deep learning algorithms to analyze ...