Answers.Body: <p>I would try a pair of separate deep image embeddings with a <a href="https://www.tensorflow.org/addons/api_docs/python/tfa/losses/ContrastiveLoss" rel="nofollow noreferrer">contrastive loss</a>. The idea is similar to the <a href="https://en.wikipedia.org/wiki/Siamese_neural_network" rel="nofollow noreferrer">Siamese network</a> architecture. In Siamese networks the pairs of images are of the same type - so both input images are fed through the copy of the same network. In your case the images are of different kinds, so I would just have separate nets for person images and fingerprints.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-05-22T22:26:56.123Z
Answers.LastActivityDate: 2021-05-22T22:26:56.123Z
Answers.UserDisplayName: Kostya
Body: <p>I have a dataset of two different type of images. Say, I have <strong>images of a person</strong> and <strong>his all 10 fingerprints</strong>. I want to create a relation between them to predict one from another. How I can do that and which architecture is suitable for this problem or similar type of problem.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-10-22T11:41:29.400Z
Comments.Text: I doubt you can predict a fingerprint image from a person's face, but this is still a valid question for some other datasets.
Comments.UserDisplayName: NikoNyrh
Tags: <convolutional-neural-networks><training><deep-neural-networks><neural-architecture-search>
Title: A neural network to learn the connection between two totally different type of images
UserDisplayName: Prapon
ThreadText: # A neural network to learn the connection between two totally different type of images
  
  (Asked by: username_0 on 2021-05-22)
  
  I have a dataset of two different type of images. Say, I have **images of a person** and **his all 10 fingerprints**. I want to create a relation between them to predict one from another. How I can do that and which architecture is suitable for this problem or similar type of problem.
  
  **Tags:** convolutional-neural-networks, training, deep-neural-networks, neural-architecture-search
  
  > **Comments:**
  > **username_1**: I doubt you can predict a fingerprint image from a person's face, but this is still a valid question for some other datasets.  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2021-05-22. Score: 1
  
  I would try a pair of separate deep image embeddings with a [contrastive loss](https://www.tensorflow.org/addons/api_docs/python/tfa/losses/ContrastiveLoss). The idea is similar to the [Siamese network](https://en.wikipedia.org/wiki/Siamese_neural_network) architecture. In Siamese networks the pairs of images are of the same type - so both input images are fed through the copy of the same network. In your case the images are of different kinds, so I would just have separate nets for person images and fingerprints.
  
  
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