Body: <p>I'm currently working on an iOS App where I want to detect if there is a table, chair or bench in the current camera input.</p>
  <p>My idea was to take the MobileNetV2 model and get it to classify these three categories with transfer learning in TensorFlow. Because there are cases where none of these three objects are visible, I would add a fourth class &quot;none&quot; and feed it with random pictures of different unrelated things.</p>
  <p>Is this approach a good idea, or is there a better way of doing this?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-06-23T09:51:58.417Z
Comments.Text: In the past, we had similar questions, for example, [this](https://ai.stackexchange.com/q/4889/2444), [this](https://ai.stackexchange.com/q/27942/2444) or [this](https://ai.stackexchange.com/q/26729/2444). Let me know if any of those posts is a duplicate of your post.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-06-25T06:21:14.637Z
Comments.Text: @nbro thank you for these suggestions. They were helpful for my problem :)
Comments.UserDisplayName: Robin
Tags: <tensorflow><image-recognition><transfer-learning><multiclass-classification><data-labelling>
Title: How to deal with images that do not contain any object of interest?
UserDisplayName: Robin
ThreadText: # How to deal with images that do not contain any object of interest?
  
  (Asked by: username_0 on 2021-06-22)
  
  I'm currently working on an iOS App where I want to detect if there is a table, chair or bench in the current camera input.
  
  My idea was to take the MobileNetV2 model and get it to classify these three categories with transfer learning in TensorFlow. Because there are cases where none of these three objects are visible, I would add a fourth class "none" and feed it with random pictures of different unrelated things.
  
  Is this approach a good idea, or is there a better way of doing this?
  
  **Tags:** tensorflow, image-recognition, transfer-learning, multiclass-classification, data-labelling
  > **Comments:**
  > **username_1**: In the past, we had similar questions, for example, [this](https://ai.stackexchange.com/q/4889/2444), [this](https://ai.stackexchange.com/q/27942/2444) or [this](https://ai.stackexchange.com/q/26729/2444). Let me know if any of those posts is a duplicate of your post.  
  > **username_0**: @nbro thank you for these suggestions. They were helpful for my problem :)  
  
  ---
  
  ## 0 answers
  
  