Nov 30, 2018 · In this article, we'll try to better understand the process and consequences of two-dimensional convolution, used extensively in the field of image processing. Convolution …

Mar 18, 2024 · In this article, we showed how to compute a convolution as a matrix-vector multiplication. The approach can be faster than the usual one with sliding since matrix …

The extension of one-dimensional convolutions to two dimensions requires a little thought about indexing and the like, but is ultimately the same operation. Here is an animation of a …

In this article the algorithm for a position dependent symmetric 2D convolution operator is discussed. Four implementation, for complex valued operators and data, are discussed and …

Apr 24, 2025 · A 2D Convolution operation is a widely used operation in computer vision and deep learning. It is a mathematical operation that applies a filter to an image, producing a …

This sample demonstrates how general (non-separable) 2D convolution with large convolution kernel sizes can be efficiently implemented in CUDA using CUFFT library.

This repository contains the implementation and analysis of 2D convolution algorithms using CUDA, focusing on optimizing performance through shared memory utilization. The study was …

•Analogue in 2D: Laplacian •Marr-Hildreth edge detector ∇2𝑓𝑥,𝑦= 𝜕2𝑓 𝜕 2𝑥 + 𝜕2𝑓 𝜕𝑦

Apr 6, 2019 · In this article, I will explain how 2D Convolutions are implemented as matrix multiplications. This explanation is based on the notes of the CS231n Convolutional Neural …

We then developed an e cient GEMM-based 2D convo- lution algorithm in a general setting. On relatively large kernels (30 ˘50-pixel wide), im2tensor is, to the best of our knowledge, the …