Convolutions

Convolution

A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the part of the input it is on, then summing the results into an output.

Intuitively, a convolution allows for weight sharing - reducing the number of effective parameters - and image translation (allowing for the same feature to be detected in different parts of the input space).

Image Source: https://arxiv.org/pdf/1603.07285.pdf

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
Semantic Segmentation 52 7.53%
Object Detection 40 5.79%
Image Segmentation 25 3.62%
Image Generation 22 3.18%
Image Classification 21 3.04%
Denoising 16 2.32%
Super-Resolution 14 2.03%
Classification 11 1.59%
Self-Supervised Learning 11 1.59%

Components


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

Categories