Receptive field

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Case study notes

Introduction

Receptive fields used in an artificial neural networks are similar to the biological explanation. They are a sensory neuron where a prompt, or stimulation, changes the action of the neuron. In other words, the fields gather information to be used by the neurons. They are used in relation to convolutional neural networks (CNNs). The neurons are arranged in a 3-D array.

How does it work or a deeper look

The receptive field gathers information and sends the information to the neurons in the CNNs. Rather than a more traditional neural network where every input neuron is linked to every other neuron at the first level, Receptive fields allow for "pre-processing" of just a certain grid (or part) of the input image.

Examples

The Gaussian receptive fields are being used in test on cars to allow them to be detected.

Pictures, diagrams

1. An image showing the arrangement of neurons in the CNN.
2. An image showing the receptive field and the CNN.

External links

• http://www.inase.org/library/2015/books/bypaper/MCSI/MCSI-42.pdf
• https://en.wikipedia.org/wiki/Receptive_field
• https://en.wikipedia.org/wiki/Receptive_field#In_the_context_of_neural_networks
• https://en.wikipedia.org/wiki/Convolutional_neural_network

Devote time and attention to gaining knowledge of (an academic subject), especially by means of books

a group or system of interconnected people or things.

a group or system of interconnected people or things.