Local pattern

As explained in Deep Learning with Python, Third Edition

A pattern that occurs within a limited neighborhood of the input rather than across the whole input space.

A local pattern is a feature found within a limited neighborhood of an input rather than across the whole input. In images, convolutional layers detect patterns in small windows, such as 3 × 3 regions, and apply the same transformation at every location. section 8.1.1

Local patterns make image recognition practical in three important ways:

• They support translation-invariant recognition: a learned edge or texture can be recognized in a different position. section 8.1.1
• They build spatial hierarchies: early layers detect edges and textures, while later layers combine them into larger visual concepts. section 8.1.1
• They produce feature maps by extracting patches from an input and transforming each patch into output channels. section 8.1.1

Figure 8.1 Images can be broken into local patterns such as edges, textures, and so on.

Use the figure to visualize images as collections of local features, including edges and textures. section 8.1.1

How Deep Learning with Python, Third Edition covers it

How deep it goes

Defines local patches, explains shared transformations and feature maps, and connects them to hierarchical visual learning.

Examples

Uses 3 × 3 image windows, edges, textures, RGB channels, and increasingly complex visual concepts.

What you can do after

Understand how convolutional layers detect and combine local image features across an input.

How it connects

Connects convolutional layers with dense layers, translation invariance, feature maps, and spatial hierarchies.

liveBookmanning.com

Read Deep Learning with Python, Third Edition on liveBook Get the book at manning.com

Also explained in

• 

  liveBookmanning.com
  Math and Architectures of Deep LearningA pattern that is confined to a small neighborhood of the input and can be captured by a local operator such as convolution.

Compare how 2 books explain local pattern →

Related concepts

• long-range dependencycontrasts with · A long-range dependency is a relationship between elements separated by substantial distance in a sequence or other structured representation that are jointly relevant.
• convolutional layerused by · A convolutional layer is a neural-network layer that applies shared learned filters to local regions of structured input to produce feature representations.
• convolutional neural networkproduced by · A convolutional neural network is a neural-network architecture that applies learned convolutional operations to extract patterns from structured data.

This explainer was generated by Manning's knowledge graph from the text of Deep Learning with Python, Third Edition. The section links point to the parts of the book it draws on.