The Emergence Machine

Convolutional Network

abstract · Computing · Level 11 · E10

E10Institutions

Each concept here is mapped to its prerequisites — the ideas you'd need first to understand it — all the way down to four foundations: Space, Time, Energy, Pattern. Click any prerequisite to drill down, or scroll for the chain graph.

Trace. Question. Emerge.

Emergence definition

convolutional-network requires neural-network, computation.

Compare Convolutional Network with…

Wiktionary senses

External reference — all senses of the word “convolutional network” on Wiktionary. This atlas concept maps to only the slice of meaning relevant to the prerequisite graph.

Loading senses…

Source: Wiktionary — “convolutional network”. Content available under CC BY-SA 4.0.

Historical origin

Origin word
convolutional network
Origin language
English

Prerequisite chain

Possible path of this concept down to the fundamental substrate.

thisfoundationsL11L10L9L8L3L2L1L0Convolutional Ne…ArchitectureArtNeural NetworkSkillCausalityCellNetworkSystem… intermediate l…FormLifeProcessStructureActionChangeExistenceMatterEnergyPatternSpaceTimeE1 concrete → E14 abstract

Neighborhood

Direct prerequisites above, concepts that depend on this one below.

thisprerequisitesConvolutional Ne…L11NetworkL3Neural NetworkL8ArchitectureL10E1 concrete → E14 abstract

In other languages

Prerequisites

What you need to understand first.

  • Network L3 (requires) Technology sense
    A convolutional network is a type of neural network architecture that applies localized filters to grid-structured data, such as images, to extract features through a series of convolutional and pooling operations.
  • Neural Network L8 (requires)
    A convolutional neural network (CNN) is a neural network architecture optimized for processing grid-structured data, particularly images, through localized filter operations.
  • Architecture L10 (requires) polysemous
    A convolutional network is a type of neural network architecture that applies localized filters to grid-structured data, such as images, to extract features through a series of convolutional and pooling operations.