CODEWITHSUNDEEP
tensorflowmachine-learningdeep-learningcomputer-visionconv-neural-network
Adelov
Adelov

Reputation: 395

Is it possible to feed multiple images input to convolutional neural network

I have a dataset of many images where images have 5 magnifications (x10, x20, x30, x40, x50) to the same class but they are not a sequence data, and all images are in RGB mode and with size 512x512 and I want to give this 5 images as an input to the CNN, and I don't know how. Also, there is another problem which is once the model was well trained on the 5 image pipeline, is it okay or will it work, when I have only one image (one magnification, x10 as an example)?

Upvotes: 7

Views: 10734

Answers (1)

alift
alift

Reputation: 1928

You have asked two questions. For the 1st one, there are two ways to do it. 1- you can design the model in a way that the input size is 5×512×512×3, and you go to train the model.

For your 2nd question, you need to design your model in a way to handle a feature absence or missing features. For a complicated one, that I can think about, you can design the model in this way, You have 5 inputs, per image, and each image goes through one or more CNN, and after one or a few layers you merge those together. For each input, you can consider an additional feature, a boolean to indicate if this current image should be considered in training or not ( is absent or present). During your training, you should make a combination of all 5, and also consider the absence of some, so that your model learns to handle the absence of one or more images out of 5 in the input. I hope I was clear enough and it helps. Good luck.

Upvotes: 5

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