Answers.Body: <blockquote>
    <p>can I use a different architecture for the decoder, or will this
    introduce weird artifacts?</p>
  </blockquote>
  
  <p>If you are using <a href="https://arxiv.org/abs/1505.04597" rel="nofollow noreferrer">U-net</a> -like architecture with skip connection from corresponding encoding to decoding layer outputs of corresponding layers should have the same spatial resolution. There is no other commonly recognized limitations on decoder architecture for convolutional networks.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-06-10T18:07:31.793Z
Answers.Text: So if I would like to add skip connection I just have to make sure the dimensions are corresponding?
Answers.UserDisplayName: oezguensi
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-06-10T19:50:26.007Z
Answers.Text: Yes, otherwise you will not be able to concatenate skip with output by channels, which is whole point of the skip connection
Answers.UserDisplayName: mirror2image
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-05-06T23:09:32.177Z
Answers.Text: Hi could you take a look here? https://ai.stackexchange.com/questions/27687/visualisation-for-mobilenet-feature-extraction
Answers.UserDisplayName: x89
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Answers.CreationDate: 2019-06-10T10:24:05.363Z
Answers.LastActivityDate: 2019-06-10T10:24:05.363Z
Answers.UserDisplayName: mirror2image
Answers.Body: <p>Other replies are commenting on the skip connections for a U-Net. I believe you want to exclude these skip connections from your auto-encoder. You say you want to use the auto-encoder for unsupervised pretraining, for which you want to pass the data through a bottle neck, so adding skip connections would work against you if you want to use the encoder for a classification task.</p>
  
  <p>You ask whether the decoder should 'mirror' the MobileNet encoder. This is actually an interesting one, and I think it could work even if the decoder does not look like the encoder at all. Since you don't need to (and in fact shouldn't) add skip connections, this should be easy to try.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-05-06T23:09:44.373Z
Answers.Text: Hi could you take a look here? https://ai.stackexchange.com/questions/27687/visualisation-for-mobilenet-feature-extraction
Answers.UserDisplayName: x89
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Answers.CreationDate: 2019-11-11T15:47:29.183Z
Answers.LastActivityDate: 2019-11-11T15:47:29.183Z
Answers.UserDisplayName: rknoops
Body: <p>I have way more unlabeled data than labeled data. Therefore I would like to train an autoencoder using MobileNetV2 as the encoder. Then I will use the pre-trained model for the classification of the labeled data.</p>
  <p>I think it is rather difficult to &quot;invert&quot; the MobileNet architecture to create a decoder. Therefore, my question is: can I use a different architecture for the decoder, or will this introduce weird artefacts?</p>
  
Tags: <convolutional-neural-networks><computer-vision><autoencoders><mobile-net-v2>
Title: If I use MobileNetV2 for the encoder, can I use a different architecture for the decoder?
UserDisplayName: oezguensi
ThreadText: # If I use MobileNetV2 for the encoder, can I use a different architecture for the decoder?
  
  (Asked by: username_0 on 2019-06-09)
  
  I have way more unlabeled data than labeled data. Therefore I would like to train an autoencoder using MobileNetV2 as the encoder. Then I will use the pre-trained model for the classification of the labeled data.
  
  I think it is rather difficult to "invert" the MobileNet architecture to create a decoder. Therefore, my question is: can I use a different architecture for the decoder, or will this introduce weird artefacts?
  
  **Tags:** convolutional-neural-networks, computer-vision, autoencoders, mobile-net-v2
  
  ---
  
  ## 2 answers
  
  ### Answer by username_1 on 2019-06-10. Score: 1 | Accepted answer
  
  > can I use a different architecture for the decoder, or will this
  > introduce weird artifacts?
  
  If you are using [U-net](https://arxiv.org/abs/1505.04597) -like architecture with skip connection from corresponding encoding to decoding layer outputs of corresponding layers should have the same spatial resolution. There is no other commonly recognized limitations on decoder architecture for convolutional networks.
  
  > **Comments:**
  > **username_0**: So if I would like to add skip connection I just have to make sure the dimensions are corresponding?  
  > **username_1**: Yes, otherwise you will not be able to concatenate skip with output by channels, which is whole point of the skip connection  
  > **username_2**: Hi could you take a look here? https://ai.stackexchange.com/questions/27687/visualisation-for-mobilenet-feature-extraction  
  
  ---
  
  ### Answer by username_3 on 2019-11-11. Score: 2
  
  Other replies are commenting on the skip connections for a U-Net. I believe you want to exclude these skip connections from your auto-encoder. You say you want to use the auto-encoder for unsupervised pretraining, for which you want to pass the data through a bottle neck, so adding skip connections would work against you if you want to use the encoder for a classification task.
  
  You ask whether the decoder should 'mirror' the MobileNet encoder. This is actually an interesting one, and I think it could work even if the decoder does not look like the encoder at all. Since you don't need to (and in fact shouldn't) add skip connections, this should be easy to try.
  
  > **Comments:**
  > **username_2**: Hi could you take a look here? https://ai.stackexchange.com/questions/27687/visualisation-for-mobilenet-feature-extraction  
  
  ---
  
  