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 50 5.85%
Object Detection 36 4.22%
Computational Efficiency 27 3.16%
Image Segmentation 24 2.81%
Denoising 21 2.46%
Image Classification 17 1.99%
Image Generation 16 1.87%
Medical Image Segmentation 16 1.87%
Deep Learning 13 1.52%

Components


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

Categories