Body: <p>I know perceptron is a linear classifier that tells linearly separable binary class data, such as iris setosa vs. iris versicolor via their sepal's length and width.</p>
  <p>I'd just like to know if I have 2 groups of photos, one is for dog and the other is for cat, is it possible to train a perceptron to tell if a picture is a dog or cat?</p>
  <p><a href="https://i.sstatic.net/zUCAr.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/zUCAr.png" alt="enter image description here" /></a></p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-06-09T11:42:24.993Z
Comments.Text: Hello. What do you mean by "iris photos, one is for dog and the other is for cat", if the iris dataset is not a dataset that contains photos of dog and cat? I guess that's a typo, but I just wanted you to clarify this.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-06-09T12:02:43.453Z
Comments.Text: I would say in general no, but it depends on the data. If all pictures of dogs have a certain colour etc. and all cats a different colour then they can certainly be separated. A single perceptron is not going to be able to detect shapes though, that's what conv nets are for
Comments.UserDisplayName: Cameron Chandler
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-06-09T12:20:06.063Z
Comments.Text: It probably is possible but will have 80-90% accuracy while a CNN should get 98% + accuracy.
Comments.UserDisplayName: Ubikuity
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-06-09T16:22:06.133Z
Comments.Text: If you really want to know just follow this tutorial https://machinelearningmastery.com/how-to-develop-a-convolutional-neural-network-to-classify-photos-of-dogs-and-cats/ and make the model a vanilla perception. You'll run into a couple snags though. The perceptron requires a fixed-size set of weights so you'll need to resale the image to something know if you really want to try this.
Comments.UserDisplayName: juicedatom
Tags: <image-recognition><perceptron>
Title: Is it possible to train a perceptron to tell if a picture is a dog or cat?
UserDisplayName: JJJohn
ThreadText: # Is it possible to train a perceptron to tell if a picture is a dog or cat?
  
  (Asked by: username_0 on 2021-06-09)
  
  I know perceptron is a linear classifier that tells linearly separable binary class data, such as iris setosa vs. iris versicolor via their sepal's length and width.
  
  I'd just like to know if I have 2 groups of photos, one is for dog and the other is for cat, is it possible to train a perceptron to tell if a picture is a dog or cat?
  
  [![enter image description here](https://i.sstatic.net/zUCAr.png)](https://i.sstatic.net/zUCAr.png)
  
  **Tags:** image-recognition, perceptron
  > **Comments:**
  > **username_1**: Hello. What do you mean by "iris photos, one is for dog and the other is for cat", if the iris dataset is not a dataset that contains photos of dog and cat? I guess that's a typo, but I just wanted you to clarify this.  
  > **username_2**: I would say in general no, but it depends on the data. If all pictures of dogs have a certain colour etc. and all cats a different colour then they can certainly be separated. A single perceptron is not going to be able to detect shapes though, that's what conv nets are for  
  > **username_3**: It probably is possible but will have 80-90% accuracy while a CNN should get 98% + accuracy.  
  > **username_4**: If you really want to know just follow this tutorial https://machinelearningmastery.com/how-to-develop-a-convolutional-neural-network-to-classify-photos-of-dogs-and-cats/ and make the model a vanilla perception. You'll run into a couple snags though. The perceptron requires a fixed-size set of weights so you'll need to resale the image to something know if you really want to try this.  
  
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  ## 0 answers
  
  