Residual neural network
id:
residual-neural-network-185-2923676
title:
Residual neural network
text:
A residual neural network is a deep learning architecture in which the weight layers learn residual functions with reference to the layer inputs. It was developed in 2015 for image recognition and won that year's ImageNet Large Scale Visual Recognition Challenge (ILSVRC). As a point of terminology, "residual connection" refers to the specific architectural motif of x ↦ f + x, where f is an arbitrary neural network module. It is a special case of the "short-cut connection" or "skip connection" by
brand slug:
wiki
category slug:
encyclopedia
description:
Deep learning method
original url:
https://en.wikipedia.org/wiki/Residual_neural_network
date created:
2017-11-23T06:14:45Z
date modified:
2024-09-07T15:30:21Z
main entity:
{"identifier":"Q43744058","url":"https://www.wikidata.org/entity/Q43744058"}
image:
{"content_url":"https://upload.wikimedia.org/wikipedia/commons/b/ba/ResBlock.png","width":1652,"height":895}
fields total:
13
integrity:
16