CODEWITHSUNDEEP
pythonmachine-learningimage-processingdeep-learningcomputer-vision
Hamza
Hamza

Reputation: 560

Do neural networks accepts other than fixed size of input data?

I am implementing a MultiLayer Perceptron , I am extracting the features of images using SIFT algorithm of image processing and I pass those features to the neural network , the features of images that I am considering are descriptors ,every image has different length of descriptors , some image has 200 descriptors and some image has 240 descriptors , means it's varying . But neural networks accepts fixed size of input data . How can I pass this type of input to it if it accept varied input then how ?

Upvotes: 0

Views: 548

Answers (2)

Igor
Igor

Reputation: 43

I think this is the questions (and answers) you are looking for are below:

But in your case, at the end you could get rid of the problem by simply using some image embedding. You could take some neural net that is pre-trained for example, Inception v3 that extracts N features from image, and you will always have constant input, of N features.

Upvotes: 1

邓剑波
邓剑波

Reputation: 11

I think you could try to pad your data to a fixed size(like the maximum length of your descriptors) vector with all 0 or mean value of this vector.

Upvotes: 0

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