CODEWITHSUNDEEP
perceptron
Anselme Clergeot
Anselme Clergeot

Reputation: 75

Perceptron and shape recognition

I recently implemented a simple Perceptron. This type of perceptron (composed of only one neuron giving binary information in output) can only solve problems where classes can be linearly separable.

I would like to implement a simple shape recognition in images of 8 by 8 pixels. I would like for example my neural network to be able to tell me if what I drawn is a circle, or not.

How to know if this problem has classes being linearly separable ? Because there is 64 inputs, can it still be linearly separable ? Can a simple perceptron solve this kind of problem ? If not, what kind of perceptron can ? I am a bit confused about that.

Thank you !

Upvotes: 1

Views: 288

Answers (1)

Hirsh
Hirsh

Reputation: 186

This problem, in a general sense, can not be solved by a single layer perception. In general other network structures such as convolutional neural networks are best for solving image classification problems, however given the small size of your images a multilayer perception may be sufficient.

Most problems are linearly separable, but not necessarily in 2 dimensions. Adding extra layers to a network allows it to transform data in higher dimensions so that it is linearly separable.

Look into multilayer perceptrons or convolutional neural networks. Examples of classification on the MNIST dataset might be helpful as well.

Upvotes: 1

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